# Tiger Data Docs

## Docs

- [Build with Tiger Data](/docs/build/index.md): Task-oriented guides organized by what you want to get done
- [Set up hypercore](/docs/build/columnar-storage/setup-hypercore/index.md): Reduce chunk size by up to 98% and speed up queries by converting data between the rowstore and columnstore
- [Convert continuous aggregates to the columnstore](/docs/build/continuous-aggregates/compression-on-continuous-aggregates/index.md): Compress a continuous aggregate to the columnstore to save storage space while making sure the data is still available for your analytical workloads
- [Create a continuous aggregate](/docs/build/continuous-aggregates/create-a-continuous-aggregate/index.md): Create a continuous aggregate and make sure you always have the latest aggregated data for your analytical queries
- [Create an index on a continuous aggregate](/docs/build/continuous-aggregates/create-index/index.md): Adding an index to your continuous aggregate can make your analytical queries lightning fast
- [Drop data from continuous aggregates](/docs/build/continuous-aggregates/drop-data/index.md): Drop a view or raw data from a continuous aggregate or its underlying hypertable
- [Migrate a continuous aggregate to the new form](/docs/build/continuous-aggregates/migrate-to-new-form/index.md): Migrate your old continuous aggregates to the new form introduced in TimescaleDB 2.7
- [Refresh continuous aggregates](/docs/build/continuous-aggregates/refresh-policies/index.md): Set up automatic refresh policies or refresh your aggregates manually to keep your data up to date
- [Cost optimization](/docs/build/cost-optimization/index.md): Reduce storage and compute costs
- [Write and query data](/docs/build/data-management/index.md): Insert, update, delete, and query time-series data in hypertables
- [About automation](/docs/build/data-management/about-automation/index.md): Automate refresh, hypercore, retention, and custom tasks with scheduled jobs
- [Create and manage custom jobs](/docs/build/data-management/create-and-manage-jobs/index.md): Create, register, test, alter, and delete custom jobs in TimescaleDB
- [Add a data retention policy](/docs/build/data-management/data-retention/create-a-retention-policy/index.md): Create a data retention policy to automatically drop historical data from your hypertables when it reaches a certain age
- [Create a custom job to downsample and compress chunks](/docs/build/data-management/example-downsample-and-compress/index.md): Downsample and convert hypertable chunks to the columnstore by combining a continuous aggregate refresh policy with hypercore
- [Create a custom retention job](/docs/build/data-management/example-generic-retention/index.md): Create a generic data retention policy for your entire database using a custom job
- [Create a custom job for automatic tablespace management](/docs/build/data-management/example-tiered-storage/index.md): Automatically move hypertable chunks between tablespaces with a custom job
- [Hyperfunctions overview](/docs/build/data-management/hyperfunctions/index.md): TimescaleDB hyperfunctions are high-performance, SQL-native functions purpose-built for time-series analysis
- [Counter aggregation](/docs/build/data-management/hyperfunctions/counter-aggregation/index.md): Collect data from counters in spite of interruptions or resets
- [Function pipelines](/docs/build/data-management/hyperfunctions/function-pipelines/index.md): Use function pipelines to improve how you write data analysis queries in PostgreSQL
- [Overview](/docs/build/data-management/hyperfunctions/gapfilling-interpolation/index.md): Handle missing data in time-series queries
- [Last observation carried forward](/docs/build/data-management/hyperfunctions/gapfilling-interpolation/locf/index.md): Fill gaps in your data by carrying the last observation forward
- [Time bucket gapfill](/docs/build/data-management/hyperfunctions/gapfilling-interpolation/time-bucket-gapfill/index.md): Use gapfilling to create contiguous time buckets and fill missing data with interpolation or LOCF
- [Heartbeat aggregation](/docs/build/data-management/hyperfunctions/heartbeat-agg/index.md): Analyze intermittent or irregular time-series data to determine system health over a given interval
- [Approximate count distincts with Hyperloglog](/docs/build/data-management/hyperfunctions/hyperloglog/index.md): Use Hyperloglog to estimate cardinality of large datasets with reduced memory consumption and improved compute time
- [Overview](/docs/build/data-management/hyperfunctions/percentile-approx/index.md): Approximate percentiles on large datasets without requiring all the data
- [Percentile approximation advanced aggregation methods](/docs/build/data-management/hyperfunctions/percentile-approx/advanced-agg/index.md): Understand the difference between uddsketch and tdigest to choose the right algorithm
- [Approximate percentiles](/docs/build/data-management/hyperfunctions/percentile-approx/approximate-percentile/index.md): Construct and run approximate percentage queries using uddsketch or tdigest
- [Statistical aggregation](/docs/build/data-management/hyperfunctions/stats-aggs/index.md): Use common statistical aggregates in window functions and continuous aggregates
- [Time-weighted averages and integrals](/docs/build/data-management/hyperfunctions/time-weighted-averages/index.md): Use time-weighted averages and integrals for time-series data that is not evenly sampled
- [Perform advanced analytic queries](/docs/build/data-management/query-data/advanced-analytic-queries/index.md): Calculate percentiles, moving averages, histograms, gap filling, and more with SQL
- [SELECT data](/docs/build/data-management/query-data/select/index.md): Query data from a hypertable using the standard SELECT command
- [Run your queries from Tiger Console](/docs/build/data-management/run-queries-from-tiger-console/index.md): Choose the right tool to manage your data. Tiger Cloud offers Data view, SQL editor, and SQL assistant to better address your needs
- [Manage storage and tiering](/docs/build/data-management/storage/manage-storage/index.md): Configure high-performance and low-cost object storage tiers in Tiger Console
- [Query tiered data](/docs/build/data-management/storage/query-tiered-data/index.md): Query data stored in the low-cost object storage tier using standard SQL
- [Replicas and forks with tiered data](/docs/build/data-management/storage/tiered-data-replicas-forks/index.md): Tiering data to object storage means your replicas and forks share the same low-cost data without additional storage costs
- [Delete data](/docs/build/data-management/write-data/delete/index.md): Delete data with DELETE or by dropping chunks from a hypertable in your database using SQL
- [Insert data](/docs/build/data-management/write-data/insert/index.md): Insert single and multiple rows and bulk load data into TimescaleDB with SQL
- [Update data](/docs/build/data-management/write-data/update/index.md): Update single and multiple rows in a hypertable in your TimescaleDB database with SQL
- [Upsert data](/docs/build/data-management/write-data/upsert/index.md): Insert a new row or update an existing row in a hypertable using UPSERT
- [Tutorials](/docs/build/examples/index.md): End-to-end projects that combine multiple features on real-world datasets
- [Aggregate organizational data with AI agents](/docs/build/examples/aggregate-organizational-data-with-ai/index.md): Unify company knowledge with Slack-native AI agents using Tiger Eon and Tiger Cloud.
- [Analyze Bitcoin blockchain](/docs/build/examples/analyze-blockchain/index.md): Query and analyze blockchain transactions to discover insights about fees, mining revenue, and market trends
- [Analyze energy consumption](/docs/build/examples/analyze-energy-consumption/index.md): Get insights from energy consumption data with Grafana and Tiger Cloud
- [Analyze application events with UUIDv7](/docs/build/examples/analyze-events-with-uuidv7/index.md): Get started with TimescaleDB using application event data and UUIDv7 identifiers, with no separate timestamp column
- [Visualize financial tick data with Grafana](/docs/build/examples/analyze-financial-tick-data/index.md): Store financial tick data, create candlestick views, and visualize price changes in Grafana
- [Analyze NYC taxi data](/docs/build/examples/analyze-nyc-taxi-data/index.md): Get started with TimescaleDB using New York City taxi trip data, with location-based analytics and time-series aggregations
- [Analyze stock market data](/docs/build/examples/analyze-stock-market-data/index.md): Analyze financial tick and candlestick data with TimescaleDB using S&P 500 stock prices
- [Visualize transport and geospatial data with Grafana](/docs/build/examples/analyze-transport-data/index.md): Simulate and analyze a transport dataset in Tiger Cloud and visualize it in Grafana
- [Tiger Data cookbook](/docs/build/examples/cookbook/index.md): Browse code examples from the Tiger community that resolve common issues and provide solutions for non-standard tasks
- [Create Tiger Cloud services with the Terraform provider](/docs/build/examples/create-services-with-terraform/index.md): Use the Tiger Data Terraform provider to deploy, manage, and destroy Tiger Cloud services using infrastructure as code.
- [Build hybrid search with BM25 and vector similarity](/docs/build/examples/hybrid-search/index.md): Combine keyword search and semantic vector search in PostgreSQL using pg_textsearch and pgvectorscale, fused with Reciprocal Rank Fusion.
- [Ingest real-time financial data](/docs/build/examples/ingest-real-time-financial-data/index.md): Set up a data pipeline to get data from different financial APIs
- [Simulate an IoT sensor dataset](/docs/build/examples/simulate-iot-sensor-data/index.md): Simulate an IoT sensor dataset for testing and development with Tiger Cloud
- [Quickstarts](/docs/build/how-to/index.md): Short, hands-on guides that walk you through a single task from start to finish
- [Basic compression with hypercore](/docs/build/how-to/basic-compression/index.md): Compress data into the columnstore for up to 98% storage savings and faster analytical queries
- [Your first hypertable](/docs/build/how-to/your-first-hypertable/index.md): Learn what hypertables are, why they matter, and create your first one step by step
- [Performance optimization](/docs/build/performance-optimization/index.md): Diagnose and optimize query performance
- [Alter and update table schemas](/docs/build/performance-optimization/alter-update-table-schema/index.md): Modify the schema of an existing hypertable with the ALTER TABLE command in PostgreSQL
- [Automate tasks with triggers](/docs/build/performance-optimization/automate-tasks-with-triggers/index.md): Use PostgreSQL triggers to automatically execute functions when data changes occur in TimescaleDB hypertables
- [Automatically route queries to continuous aggregates](/docs/build/performance-optimization/cagg-query-rewrites/index.md): Have TimescaleDB transparently route matching queries to a continuous aggregate instead of the raw hypertable
- [Ensure data integrity with constraints](/docs/build/performance-optimization/ensure-data-integrity-with-constraints/index.md): Prevent invalid data by applying rules to your table columns using PostgreSQL constraints
- [Handle semi-structured data with JSON](/docs/build/performance-optimization/handle-semi-structured-data-with-json/index.md): Use JSON or JSONB to store semi-structured data, such as user-defined fields, and learn how to index the JSONB structure and individual fields
- [Enforce constraints with unique indexes](/docs/build/performance-optimization/hypertables-and-unique-indexes/index.md): Having a unique index on your hypertable simplifies lookup, speeds up aggregation, and makes JOINs more efficient. Learn to create a unique index and what the related limitations are.
- [Improve hypertable and query performance](/docs/build/performance-optimization/improve-hypertable-performance/index.md): Use chunk skipping to optimize hypertable performance and make sure your analytical queries are as fast as they can be
- [Accelerate queries using indexes](/docs/build/performance-optimization/indexing/index.md): Add indexes to speed up queries and DML on your hypertables — different mechanisms apply to the rowstore and the columnstore
- [Improve storage performance using tablespaces](/docs/build/performance-optimization/manage-tablespaces/index.md): Store database objects in specific physical locations on disk using tablespaces for PostgreSQL hypertable chunks
- [Query external data sources with FDW](/docs/build/performance-optimization/query-external-data-sources-with-fdw/index.md): Query other Tiger Cloud services or external PostgreSQL databases using foreign data wrappers
- [Retrofit chunk intervals on a production hypertable](/docs/build/performance-optimization/retrofit-chunk-intervals/index.md): Increase the chunk_interval of an existing hypertable without blocking ingestion, using a table-swap migration and batched backfill.
- [Improve query and upsert performance](/docs/build/performance-optimization/secondary-indexes/index.md): Use segmenting and ordering data in the columnstore to make lookup queries and upserts faster
- [Get faster DISTINCT queries with SkipScan](/docs/build/performance-optimization/skipscan/index.md): Speed up DISTINCT queries with the SkipScan optimization
- [Best practices for AI agents](/docs/build/tiger-cli-mcp/agent-best-practices/index.md): Use Tiger MCP and Tiger CLI safely with AI agents, including read-only mode, forks and read replicas, and effective prompting
- [Common tasks with Tiger CLI and Tiger MCP](/docs/build/tiger-cli-mcp/common-tasks/index.md): Manage services and work with your data in Tiger Cloud using Tiger CLI commands or Tiger MCP natural-language prompts
- [Tiger CLI and MCP cookbook](/docs/build/tiger-cli-mcp/cookbook/index.md): Copy-paste prompts for Tiger MCP that design a schema, analyze your data, compare performance, test safely with forks, and tune a service
- [Troubleshooting](/docs/build/tips-and-tricks/index.md): Diagnose and fix common Tiger Data problems
- [Troubleshoot continuous aggregates](/docs/build/tips-and-tricks/troubleshoot-continuous-aggregates/index.md): Troubleshoot common problems with continuous aggregates
- [Troubleshoot data retention](/docs/build/tips-and-tricks/troubleshoot-data-retention/index.md): Find the solutions to common errors when working with data retention policies
- [Troubleshoot data tiering](/docs/build/tips-and-tricks/troubleshoot-data-tiering/index.md): Solutions to common errors when working with tiered storage
- [Troubleshoot hypercore](/docs/build/tips-and-tricks/troubleshoot-hypercore/index.md): Resolve common issues with hypercore, columnstore conversion, and compression
- [Troubleshoot hyperfunctions](/docs/build/tips-and-tricks/troubleshoot-hyperfunctions/index.md): Solutions to common errors with hyperfunctions and TimescaleDB Toolkit
- [Troubleshoot hypertables](/docs/build/tips-and-tricks/troubleshoot-hypertables/index.md): Solutions to common errors and fixes for hypertables, chunks, compression, and permissions.
- [Troubleshoot import and ingest](/docs/build/tips-and-tricks/troubleshoot-import-ingest/index.md): Solutions to common errors when importing data and migrating databases
- [Troubleshoot jobs](/docs/build/tips-and-tricks/troubleshoot-jobs/index.md): Solutions to common errors when working with scheduled jobs
- [Troubleshoot queries](/docs/build/tips-and-tricks/troubleshoot-query-data/index.md): Resolve common issues with querying data in TimescaleDB
- [Troubleshoot schema management](/docs/build/tips-and-tricks/troubleshoot-schema-management/index.md): Resolve common issues with database schemas and indexes
- [Troubleshoot time buckets](/docs/build/tips-and-tricks/troubleshoot-time-buckets/index.md): Troubleshoot common problems with time buckets
- [Deploy Tiger Data products](/docs/deploy/index.md): Choose your deployment option
- [Tiger Cloud](/docs/deploy-and-operate/index.md): Robust elastic cloud platform for startups and enterprise
- [Limitations](/docs/deploy/limitations/index.md): Current limitations of Tiger Data products
- [Managed Service for TimescaleDB](/docs/deploy/mst/index.md): Install, configure, and manage TimescaleDB managed by Aiven
- [About MST](/docs/deploy/mst/about-mst/index.md): Set up and manage your services in Managed Service for TimescaleDB
- [Aiven Client](/docs/deploy/mst/aiven-client/index.md): Manage your services in the Managed Service for TimescaleDB with a command-line tool
- [Billing](/docs/deploy/mst/billing/index.md): Billing and account management in Managed Service for TimescaleDB
- [Connection pools](/docs/deploy/mst/connection-pools/index.md): Pool client connections to your service in Managed Service for TimescaleDB to use less server resources
- [Create an MST service](/docs/deploy/mst/create-mst-service/index.md): Create and connect to a service in Managed Service for TimescaleDB
- [Use the Postgres dblink extension](/docs/deploy/mst/dblink-extension/index.md): Use the dblink extension and connect to other Postgres databases
- [Supported extensions](/docs/deploy/mst/extensions/index.md): Add an extension and see a list of available extensions in Managed Service for TimescaleDB
- [Failover](/docs/deploy/mst/failover/index.md): Learn how failover to a read-only replica ensures business continuity for your services running in Managed Service for TimescaleDB
- [Identify and repair issues with PostgreSQL indexes with REINDEX](/docs/deploy/mst/identify-index-issues/index.md): Identify and resolve issues with Postgres indexes in Managed Service for TimescaleDB
- [Ingest data](/docs/deploy/mst/ingest-data/index.md): Ingest data into your services running in Managed Service for TimescaleDB
- [Integrations](/docs/deploy/mst/integrations/index.md): Integrate Managed Service for TimescaleDB with other services
- [Visualize data with Google Data Studio](/docs/deploy/mst/integrations/google-data-studio-mst/index.md): Integrate Google Data Studio with Managed Service for TimescaleDB
- [Visualize data with Grafana](/docs/deploy/mst/integrations/grafana-mst/index.md): Integrate Managed Service for TimescaleDB as a data source in Grafana to visualize your data
- [Logging](/docs/deploy/mst/integrations/logging/index.md): Retrieve logging information on Managed Service for TimescaleDB
- [Send metrics to Datadog](/docs/deploy/mst/integrations/metrics-datadog/index.md): Collect Datadog metrics on your Managed Service for TimescaleDB service
- [Set up a Prometheus endpoint](/docs/deploy/mst/integrations/prometheus-mst/index.md): Use Prometheus to monitor your Managed Service for TimescaleDB
- [Maintenance](/docs/deploy/mst/maintenance/index.md): Learn how maintenance is automatically handled on Managed Service for TimescaleDB
- [Backups](/docs/deploy/mst/manage-backups/index.md): Back up your services running in the Managed Service for TimescaleDB with alternative tools
- [Migrate data from self-hosted TimescaleDB to MST](/docs/deploy/mst/migrate-to-mst/index.md): Migrate a self-hosted TimescaleDB database to Managed Service for TimescaleDB
- [Create a read-only replica](/docs/deploy/mst/postgresql-read-replica/index.md): Create and use a read-only replica for your services in Managed Service for TimescaleDB
- [REST API](/docs/deploy/mst/restapi/index.md): Use REST API for integration and automation in Managed Service for TimescaleDB
- [Security](/docs/deploy/mst/security/index.md): Learn how your Managed Service for TimescaleDB instance is secured
- [Troubleshooting](/docs/deploy/mst/troubleshooting/index.md): Troubleshoot common issues with Managed Service for TimescaleDB
- [User management](/docs/deploy/mst/user-management/index.md): Add and manage users in your Managed Service for TimescaleDB project
- [Viewing service logs](/docs/deploy/mst/viewing-service-logs/index.md): View logs for your services in Managed Service for TimescaleDB by using MST Console or the command-line tool
- [VPC peering](/docs/deploy/mst/vpc-peering/index.md): Secure your Managed Service for TimescaleDB service with VPC peering
- [Configure VPC peering](/docs/deploy/mst/vpc-peering/vpc-peering/index.md): Configure VPC peering for your services running in the Managed Service for TimescaleDB Console
- [VPC peering on AWS](/docs/deploy/mst/vpc-peering/vpc-peering-aws/index.md): Secure your Managed Service for TimescaleDB instance with VPC peering on AWS
- [AWS Transit Gateway](/docs/deploy/mst/vpc-peering/vpc-peering-aws-transit/index.md): Secure your Managed Service for TimescaleDB instance with Transit Gateway on AWS
- [VPC peering on Azure](/docs/deploy/mst/vpc-peering/vpc-peering-azure/index.md): Secure your Managed Service for TimescaleDB instance with VPC peering on Azure
- [VPC peering on GCP](/docs/deploy/mst/vpc-peering/vpc-peering-gcp/index.md): Secure your Managed Service for TimescaleDB instance with VPC peering on GCP
- [Self-hosted TimescaleDB](/docs/deploy/self-hosted/index.md): Install, configure, and manage self-hosted TimescaleDB on your own infrastructure
- [Backup and restore](/docs/deploy/self-hosted/backup-and-restore/index.md): Back up and restore your self-hosted TimescaleDB instance using logical or physical backups
- [Logical backup with pg_dump and pg_restore](/docs/deploy/self-hosted/backup-and-restore/logical-backup/index.md): Back up and restore a hypertable or an entire database using native PostgreSQL commands
- [Physical backups](/docs/deploy/self-hosted/backup-and-restore/physical/index.md): Make physical backups of your entire TimescaleDB instance with pg_basebackup or external backup and restore managers
- [Configuration](/docs/deploy/self-hosted/configuration/index.md): Configure your self-hosted TimescaleDB instance
- [About configuration in TimescaleDB](/docs/deploy/self-hosted/configuration/about-configuration/index.md): Configure your TimescaleDB instance including settings related to memory, workers, disk writes, and transactional locks
- [Configuration with Docker](/docs/deploy/self-hosted/configuration/docker-config/index.md): Configure a TimescaleDB instance running in a Docker container
- [Manual PostgreSQL configuration and tuning](/docs/deploy/self-hosted/configuration/postgres-config/index.md): Manually configure your self-hosted database using the PostgreSQL configuration file
- [Telemetry and version checking](/docs/deploy/self-hosted/configuration/telemetry/index.md): Learn what telemetry TimescaleDB collects and how to disable it
- [TimescaleDB configuration and tuning](/docs/deploy/self-hosted/configuration/timescaledb-config/index.md): Configure TimescaleDB settings related to policies, query planning and execution, and administration
- [TimescaleDB tuning tool](/docs/deploy/self-hosted/configuration/timescaledb-tune/index.md): Use timescaledb-tune to automatically configure your TimescaleDB instance based on your system's resources
- [Manage storage using tablespaces](/docs/deploy/self-hosted/manage-storage/index.md): Save on data storage by moving older chunks to cheaper, slower storage, while still using faster, more expensive storage for frequently accessed data
- [Migrate your PostgreSQL database to self-hosted TimescaleDB](/docs/deploy/self-hosted/migration/index.md): Choose how to migrate your existing PostgreSQL database to your self-hosted TimescaleDB installation
- [Migrate the entire database at once](/docs/deploy/self-hosted/migration/entire-database/index.md): Migrate a small database to self-hosted TimescaleDB in one go with pg_dump and pg_restore
- [Migrate data to TimescaleDB from InfluxDB](/docs/deploy/self-hosted/migration/migrate-influxdb/index.md): Migrate data into your self-hosted TimescaleDB installation using the Outflux tool
- [Migrate data to TimescaleDB from the same PostgreSQL instance](/docs/deploy/self-hosted/migration/same-db/index.md): Migrate data into a TimescaleDB hypertable from a regular PostgreSQL table
- [Migrate schema and data separately](/docs/deploy/self-hosted/migration/schema-then-data/index.md): Migrate your data and schema to self-hosted TimescaleDB separately for easier failure recovery
- [Replication and high availability](/docs/deploy/self-hosted/replication-and-ha/index.md): Set up replication and high availability for self-hosted TimescaleDB
- [About high availability](/docs/deploy/self-hosted/replication-and-ha/about-ha/index.md): Increase the redundancy and resilience of your TimescaleDB database with backup and replication
- [Configure replication](/docs/deploy/self-hosted/replication-and-ha/configure-replication/index.md): Set up asynchronous streaming replication on one or more database replicas in your self-hosted TimescaleDB installation
- [Additional tooling](/docs/deploy/self-hosted/tooling/index.md): Get the most out of TimescaleDB with open-source tools that help you perform common tasks
- [About timescaledb-tune](/docs/deploy/self-hosted/tooling/about-timescaledb-tune/index.md): Automatically tune your TimescaleDB database to match your system resources and PostgreSQL version
- [Install, update, and uninstall TimescaleDB Toolkit](/docs/deploy/self-hosted/tooling/install-toolkit/index.md): Install, update, and uninstall the TimescaleDB Toolkit extension to access more hyperfunctions and function pipelines
- [Troubleshooting](/docs/deploy/self-hosted/troubleshooting/index.md): Troubleshoot common problems with self-hosted TimescaleDB
- [Uninstall TimescaleDB](/docs/deploy/self-hosted/uninstall/index.md): Uninstall TimescaleDB without uninstalling PostgreSQL
- [Upgrade TimescaleDB](/docs/deploy/self-hosted/upgrades/index.md): Upgrade your self-hosted TimescaleDB installation to a minor or major version in-place, or revert to the previous minor
- [Downgrade to a previous version of TimescaleDB](/docs/deploy/self-hosted/upgrades/downgrade/index.md): Downgrade your self-hosted TimescaleDB installation to the previous minor version
- [Major TimescaleDB upgrades](/docs/deploy/self-hosted/upgrades/major-upgrade/index.md): Upgrade your self-hosted TimescaleDB installation to a new major version
- [Minor TimescaleDB upgrades](/docs/deploy/self-hosted/upgrades/minor-upgrade/index.md): Upgrade your self-hosted TimescaleDB to a new minor version
- [Upgrade TimescaleDB running in Docker](/docs/deploy/self-hosted/upgrades/upgrade-docker/index.md): Upgrade self-hosted TimescaleDB running in a Docker container to a new minor version
- [Upgrade PostgreSQL](/docs/deploy/self-hosted/upgrades/upgrade-pg/index.md): Upgrade PostgreSQL to a new version compatible with your self-hosted TimescaleDB installation
- [About configuration in Tiger Cloud](/docs/deploy/tiger-cloud/tiger-cloud-aws/configuration/about-configuration/index.md): Have your service auto-tuned or configure manually
- [Advanced parameters](/docs/deploy/tiger-cloud/tiger-cloud-aws/configuration/advanced-parameters/index.md): Tune advanced PostgreSQL parameters for your Tiger Cloud service in Tiger Console
- [Configure database parameters](/docs/deploy/tiger-cloud/tiger-cloud-aws/configuration/customize-configuration/index.md): Customize PostgreSQL and Tiger Cloud database parameters for individual services
- [Back up and recover services](/docs/deploy/tiger-cloud/tiger-cloud-aws/high-availability/backup-restore/index.md): Protect your data with automatic backups and cross-region protection
- [Manage high availability](/docs/deploy/tiger-cloud/tiger-cloud-aws/high-availability/high-availability/index.md): Configure HA replicas across availability zones to minimize downtime
- [Overview](/docs/deploy/tiger-cloud/tiger-cloud-aws/high-availability/overview/index.md): Reduce downtime risk and scale reads with database replication
- [Read scaling](/docs/deploy/tiger-cloud/tiger-cloud-aws/high-availability/read-scaling/index.md): Scale reads horizontally with read replica sets and automated load balancing
- [Monitor your services](/docs/deploy/tiger-cloud/tiger-cloud-aws/monitoring/index.md): View logs, metrics, and performance insights for your Tiger Cloud services
- [Billing and account management](/docs/deploy/tiger-cloud/tiger-cloud-aws/pricing-and-account-management/index.md): Manage billing, pricing plans, and account settings for Tiger Cloud on AWS
- [Private endpoints](/docs/deploy/tiger-cloud/tiger-cloud-aws/security/aws-privatelink/index.md): Connect your services to AWS PrivateLink endpoints to eliminate public internet exposure
- [Client credentials](/docs/deploy/tiger-cloud/tiger-cloud-aws/security/client-credentials/index.md): Create programmatic credentials to access Tiger Cloud without a password
- [IP allow list](/docs/deploy/tiger-cloud/tiger-cloud-aws/security/ip-allow-list/index.md): Restrict access to your services with IP address allow lists
- [Control user access to projects](/docs/deploy/tiger-cloud/tiger-cloud-aws/security/members/index.md): Manage project roles, add and remove users, transfer ownership, and enforce authentication requirements
- [Multi-factor authentication](/docs/deploy/tiger-cloud/tiger-cloud-aws/security/multi-factor-authentication/index.md): Set up two-factor authentication for your Tiger Cloud account
- [About security in Tiger Cloud](/docs/deploy/tiger-cloud/tiger-cloud-aws/security/overview/index.md): Learn how Tiger Cloud protects your PostgreSQL data with encryption, access controls, and network security
- [Manage data security in your service](/docs/deploy/tiger-cloud/tiger-cloud-aws/security/read-only-role/index.md): Restrict data access with read-only PostgreSQL roles
- [SAML authentication](/docs/deploy/tiger-cloud/tiger-cloud-aws/security/saml/index.md): Configure SAML single sign-on for Enterprise accounts
- [Connect with a stricter SSL mode](/docs/deploy/tiger-cloud/tiger-cloud-aws/security/strict-ssl/index.md): Use verify-ca or verify-full SSL modes for stricter connection security
- [AWS Transit Gateway](/docs/deploy/tiger-cloud/tiger-cloud-aws/security/transit-gateway/index.md): Securely connect to your services from AWS, Google Cloud, Azure, or on-premise environments using AWS Transit Gateway
- [VPC Peering](/docs/deploy/tiger-cloud/tiger-cloud-aws/security/vpc/index.md): Secure your services with Virtual Private Cloud peering
- [About Tiger Cloud services](/docs/deploy/tiger-cloud/tiger-cloud-aws/service-management/index.md): Create, manage, and scale Tiger Cloud PostgreSQL services
- [Manually change compute resources](/docs/deploy/tiger-cloud/tiger-cloud-aws/service-management/change-resources/index.md): Change the CPU and memory allocated to a service from Tiger Console or Tiger CLI
- [Connection pooling](/docs/deploy/tiger-cloud/tiger-cloud-aws/service-management/connection-pooling/index.md): Create and manage connection poolers in Tiger Console to improve database performance
- [Fork services](/docs/deploy/tiger-cloud/tiger-cloud-aws/service-management/fork-services/index.md): Fork a service to create isolated database branches for testing and development
- [Service explorer](/docs/deploy/tiger-cloud/tiger-cloud-aws/service-management/service-explorer/index.md): Monitor service health and performance with the Service Explorer dashboard
- [Service management](/docs/deploy/tiger-cloud/tiger-cloud-aws/service-management/service-management/index.md): Manage the lifecycle of your service from Tiger Console or Tiger CLI
- [Tiger Console overview](/docs/deploy/tiger-cloud/tiger-cloud-aws/service-management/service-overview/index.md): Manage access, security, and day-to-day operations for your services
- [PostgreSQL extensions](/docs/deploy/tiger-cloud/tiger-cloud-aws/tiger-cloud-extensions/index.md): Browse and enable PostgreSQL extensions available in Tiger Cloud
- [Optimize full text search with BM25](/docs/deploy/tiger-cloud/tiger-cloud-aws/tiger-cloud-extensions/pg-textsearch/index.md): Install and tune pg_textsearch (v1.1.0) for BM25 full-text search on Tiger Cloud and self-hosted deployments
- [Encrypt data using pgcrypto](/docs/deploy/tiger-cloud/tiger-cloud-aws/tiger-cloud-extensions/pgcrypto/index.md): Encrypt sensitive data in your database using the pgcrypto extension
- [Create a chatbot using pgvector](/docs/deploy/tiger-cloud/tiger-cloud-aws/tiger-cloud-extensions/pgvector/index.md): Build a chatbot with vector similarity search using the pgvector extension
- [Analyse geospatial data with PostGIS](/docs/deploy/tiger-cloud/tiger-cloud-aws/tiger-cloud-extensions/postgis/index.md): Store, query, and analyze geospatial data using the PostGIS extension
- [Maintenance and upgrades](/docs/deploy/tiger-cloud/tiger-cloud-aws/upgrades/index.md): Keep your Tiger Cloud service up to date with managed upgrades and maintenance windows
- [About configuration in Tiger Cloud](/docs/deploy/tiger-cloud/tiger-cloud-azure/configuration/about-configuration/index.md): Have your service auto-tuned or configure manually
- [Advanced parameters](/docs/deploy/tiger-cloud/tiger-cloud-azure/configuration/advanced-parameters/index.md): Tune advanced PostgreSQL parameters for your Tiger Cloud service in Tiger Console
- [Configure database parameters](/docs/deploy/tiger-cloud/tiger-cloud-azure/configuration/customize-configuration/index.md): Customize PostgreSQL and Tiger Cloud configuration options per service
- [Back up and recover services](/docs/deploy/tiger-cloud/tiger-cloud-azure/high-availability/backup-restore/index.md): Protect your data with automatic backups and cross-region protection
- [Manage high availability](/docs/deploy/tiger-cloud/tiger-cloud-azure/high-availability/high-availability/index.md): Configure HA replicas across availability zones to minimize downtime
- [Overview](/docs/deploy/tiger-cloud/tiger-cloud-azure/high-availability/overview/index.md): Reduce downtime risk and scale reads with database replication
- [Read scaling](/docs/deploy/tiger-cloud/tiger-cloud-azure/high-availability/read-scaling/index.md): Scale reads horizontally with read replica sets and automated load balancing
- [Monitor your services](/docs/deploy/tiger-cloud/tiger-cloud-azure/monitoring/index.md): View logs, metrics, and performance insights for your Tiger Cloud services
- [Billing and account management](/docs/deploy/tiger-cloud/tiger-cloud-azure/pricing-and-account-management/index.md): Manage billing, pricing plans, and account settings for Tiger Cloud on Azure
- [Private endpoints](/docs/deploy/tiger-cloud/tiger-cloud-azure/security/azure-privatelink/index.md): Connect your services to Azure Private Link endpoints to eliminate public internet exposure
- [Client credentials](/docs/deploy/tiger-cloud/tiger-cloud-azure/security/client-credentials/index.md): Create programmatic credentials to access Tiger Cloud without a password
- [IP allow list](/docs/deploy/tiger-cloud/tiger-cloud-azure/security/ip-allow-list/index.md): Restrict access to your services with IP address allow lists
- [Control user access to projects](/docs/deploy/tiger-cloud/tiger-cloud-azure/security/members/index.md): Manage project roles, add and remove users, transfer ownership, and enforce authentication requirements
- [Multi-factor authentication](/docs/deploy/tiger-cloud/tiger-cloud-azure/security/multi-factor-authentication/index.md): Set up two-factor authentication for your Tiger Cloud account
- [About security in Tiger Cloud](/docs/deploy/tiger-cloud/tiger-cloud-azure/security/overview/index.md): Learn how Tiger Cloud protects your PostgreSQL data with encryption, access controls, and network security
- [Manage data security in your service](/docs/deploy/tiger-cloud/tiger-cloud-azure/security/read-only-role/index.md): Restrict data access with read-only PostgreSQL roles
- [SAML authentication](/docs/deploy/tiger-cloud/tiger-cloud-azure/security/saml/index.md): Configure SAML single sign-on for Enterprise accounts
- [Connect with a stricter SSL mode](/docs/deploy/tiger-cloud/tiger-cloud-azure/security/strict-ssl/index.md): Use verify-ca or verify-full SSL modes for stricter connection security
- [About Tiger Cloud services](/docs/deploy/tiger-cloud/tiger-cloud-azure/service-management/index.md): Create, manage, and scale Tiger Cloud PostgreSQL service instances on Azure
- [Manually change compute resources](/docs/deploy/tiger-cloud/tiger-cloud-azure/service-management/change-resources/index.md): Change the CPU and memory allocated to a service from Tiger Console or Tiger CLI
- [Connection pooling](/docs/deploy/tiger-cloud/tiger-cloud-azure/service-management/connection-pooling/index.md): Create connection poolers in Tiger Console to reuse connections and boost performance
- [Fork services](/docs/deploy/tiger-cloud/tiger-cloud-azure/service-management/fork-services/index.md): Fork a Tiger Cloud service to create isolated branches for testing and development
- [Service explorer](/docs/deploy/tiger-cloud/tiger-cloud-azure/service-management/service-explorer/index.md): Monitor service health and performance with the Service Explorer dashboard
- [Service management](/docs/deploy/tiger-cloud/tiger-cloud-azure/service-management/service-management/index.md): Manage the lifecycle of your service from Tiger Console or Tiger CLI
- [Tiger Console overview](/docs/deploy/tiger-cloud/tiger-cloud-azure/service-management/service-overview/index.md): Manage daily operations, access control, security, and queries for Tiger Cloud services
- [PostgreSQL extensions](/docs/deploy/tiger-cloud/tiger-cloud-azure/tiger-cloud-extensions/index.md): Browse and enable PostgreSQL extensions available for Tiger Cloud services
- [Optimize full text search with BM25](/docs/deploy/tiger-cloud/tiger-cloud-azure/tiger-cloud-extensions/pg-textsearch/index.md): Install and tune pg_textsearch (v1.1.0) for BM25 full-text search on Tiger Cloud and self-hosted deployments
- [Encrypt data using pgcrypto](/docs/deploy/tiger-cloud/tiger-cloud-azure/tiger-cloud-extensions/pgcrypto/index.md): Encrypt sensitive data in your PostgreSQL database using the pgcrypto extension
- [Create a chatbot using pgvector](/docs/deploy/tiger-cloud/tiger-cloud-azure/tiger-cloud-extensions/pgvector/index.md): Build a chatbot with vector similarity search using the pgvector extension
- [Analyse geospatial data with PostGIS](/docs/deploy/tiger-cloud/tiger-cloud-azure/tiger-cloud-extensions/postgis/index.md): Store, query, and analyze geospatial data in PostgreSQL using the PostGIS extension
- [Maintenance and upgrades](/docs/deploy/tiger-cloud/tiger-cloud-azure/upgrades/index.md): Keep your Tiger Cloud service up to date with managed upgrades and maintenance windows
- [Troubleshoot Tiger Cloud](/docs/deploy/tiger-cloud/troubleshoot/index.md): Diagnose and resolve common issues with Tiger Cloud services
- [Vectorizer and in-database LLM calls migration guide](/docs/deploy/tiger-cloud/vectorizer-deprecation/index.md): Plan your move off Tiger Cloud-managed vectorizer workers and in-database LLM SQL helpers before June 30, 2026. Tables, embeddings, and vectorizer definitions stay in the database.
- [Get started with Tiger Data](/docs/get-started/index.md): Welcome to Tiger Data, choose your path to get started
- [Install self-hosted TimescaleDB](/docs/get-started/choose-your-path/install-timescaledb/index.md): Install TimescaleDB on Linux, macOS, Windows, Docker, Kubernetes, or from source
- [Compare TimescaleDB editions](/docs/get-started/choose-your-path/timescaledb-editions/index.md): See the difference between the TimescaleDB Community and TimescaleDB Apache 2 editions
- [Cloud-exclusive features](/docs/get-started/cloud-exclusive-features/index.md): Learn about the features and capabilities available exclusively in Tiger Cloud
- [Contribute to the docs](/docs/get-started/contributing/index.md): How to contribute to Tiger Data documentation, open issues, submit changes via PR, or request changelog entries
- [Feature comparison](/docs/get-started/feature-comparison/index.md): Compare features across Tiger Cloud on AWS, Tiger Cloud on Azure, and self-hosted TimescaleDB
- [News and updates](/docs/get-started/news/index.md): Changelog, release notes, and product updates for Tiger Data
- [Changelog](/docs/get-started/news/new/index.md): Get the latest updates to Tiger Cloud with links to detailed documentation
- [Release notes](/docs/get-started/news/release-notes/index.md): Get an overview of the new features, improvements, and fixes released in every version of TimescaleDB and other downloadable products
- [Connect your app](/docs/get-started/quickstart/connect-your-app/index.md): Connect your existing application to TimescaleDB
- [Create a Tiger Cloud service](/docs/get-started/quickstart/create-service/index.md): Create a Tiger Cloud account and your first service in Tiger Console
- [Integrate Tiger Cloud with your AI Agent (MCP and CLI)](/docs/get-started/quickstart/mcp-cli/index.md): Install Tiger CLI, set up Tiger MCP, and manage Tiger Cloud resources from Claude, Cursor, and other AI agents
- [5-minute quickstart](/docs/get-started/quickstart/quickstart-5-minutes/index.md): Get up and running with Tiger Cloud in 5 minutes
- [Get started with the REST API](/docs/get-started/quickstart/rest-api/index.md): Manage the resources in your Tiger Cloud project programmatically with the Tiger Cloud REST API
- [Get started with Tiger CLI](/docs/get-started/quickstart/tiger-cli/index.md): Install Tiger CLI and manage the resources in your Tiger Cloud project from the command line
- [10-minute quickstart](/docs/get-started/quickstart/timescaledb-quickstart/index.md): Get started with self-hosted TimescaleDB in about 10 minutes
- [Supported regions](/docs/get-started/supported-regions/index.md): Learn which regions are available for Tiger Cloud services
- [Supported platforms](/docs/get-started/timescaledb-supported-platforms/index.md): Operating systems and PostgreSQL versions supported by self-hosted TimescaleDB
- [Tiger Data Documentation](/docs/index.md): Postgres for time series, events, and analytics, from the creators of TimescaleDB
- [Integrate with Tiger Data](/docs/integrate/index.md): Connect Tiger Data to your stack; ETL, BI, streaming, connectors, and observability
- [BI & visualization](/docs/integrate/bi-vizualization/index.md): Use your BI and visualization tools with Tiger Data
- [Integrate Power BI with Tiger Cloud](/docs/integrate/bi-vizualization/power-bi/index.md): Create interactive reports and dashboards to analyze and share insights from your data
- [Integrate Tableau and Tiger Cloud](/docs/integrate/bi-vizualization/tableau/index.md): Visualize and analyze your data to gain business intelligence and share insights
- [Code and libraries](/docs/integrate/code/index.md): Connect applications to Tiger Data using your preferred programming language and tools
- [Connect your app](/docs/integrate/code/connect-your-app/index.md): Integrate your app with self-hosted TimescaleDB using your preferred programming language
- [Configuration & deployment](/docs/integrate/configuration-deployment/index.md): Use your IaC and deployment tools with Tiger Data
- [Integrate TimescaleDB with CloudNativePG on Kubernetes](/docs/integrate/configuration-deployment/cloudnativepg/index.md): Deploy and operate TimescaleDB on Kubernetes with CloudNativePG for production-ready time-series workloads
- [Integrate Kubernetes with Tiger Cloud](/docs/integrate/configuration-deployment/kubernetes/index.md): Automate deployment, scaling, and management of your containerized workloads
- [Integrate Terraform with Tiger Cloud](/docs/integrate/configuration-deployment/terraform/index.md): Provision and manage your infrastructure as code with predictable deployments
- [Connectors](/docs/integrate/connectors/index.md): Ingest and sync data into Tiger Data using source and destination connectors
- [Query TigerLake S3 Tables with AWS Glue and Athena](/docs/integrate/connectors/destination/athena/index.md): Expose Iceberg tables written by TigerLake to the AWS Glue Data Catalog and query them with Amazon Athena, with no ETL or data duplication.
- [Query TigerLake S3 Tables from Snowflake](/docs/integrate/connectors/destination/snowflake/index.md): Query Tiger Cloud time-series data from Snowflake using Apache Iceberg and Amazon S3 Tables, without ETL pipelines or data duplication.
- [Integrate data lakes with Tiger Cloud](/docs/integrate/connectors/destination/tigerlake/index.md): Unify the Tiger Cloud operational architecture with data lake architectures
- [Stream data from Kafka](/docs/integrate/connectors/source/sync-from-kafka/index.md): Store, query, and analyze your Apache Kafka events in Tiger Cloud
- [Sync data from Postgres](/docs/integrate/connectors/source/sync-from-postgres/index.md): Sync updates to your primary Postgres database with Tiger Cloud in real time
- [Sync data from S3](/docs/integrate/connectors/source/sync-from-s3/index.md): Sync data from S3 to your Tiger Cloud service in real time
- [Data engineering & ETL](/docs/integrate/data-engineering-etl/index.md): Use your ETL tools and data pipelines with Tiger Data
- [Integrate Amazon SageMaker with Tiger Cloud](/docs/integrate/data-engineering-etl/amazon-sagemaker/index.md): Build, train, and deploy ML models with time-series data storage and analysis
- [Integrate Apache Airflow with Tiger Cloud](/docs/integrate/data-engineering-etl/apache-airflow/index.md): Author, schedule, and monitor workflows to orchestrate your data pipelines
- [Integrate AWS Lambda with Tiger Cloud](/docs/integrate/data-engineering-etl/aws-lambda/index.md): Run serverless code to process and store your data without managing infrastructure
- [Integrate Debezium with TimescaleDB](/docs/integrate/data-engineering-etl/debezium/index.md): Capture and stream database changes in real time for event-driven architecture
- [Integrate Decodable with Tiger Cloud](/docs/integrate/data-engineering-etl/decodable/index.md): Build and manage real-time data pipelines to stream and process your data effortlessly
- [Integrate Supabase with Tiger Cloud](/docs/integrate/data-engineering-etl/supabase/index.md): Run real-time analytical queries across databases using foreign data wrappers
- [Data ingestion & streaming](/docs/integrate/data-ingestion-streaming/index.md): Use your data ingestion and streaming tools with Tiger Data
- [Integrate Apache Kafka with Tiger Cloud](/docs/integrate/data-ingestion-streaming/apache-kafka/index.md): Stream, process, and analyze real-time event data from Apache Kafka topics
- [Integrate EMQX with Tiger Cloud](/docs/integrate/data-ingestion-streaming/emqx/index.md): Connect EMQX to Tiger Cloud and stream MQTT messages into a hypertable
- [Integrate Fivetran with Tiger Cloud](/docs/integrate/data-ingestion-streaming/fivetran/index.md): Automatically sync data from multiple sources to simplify ETL processes
- [Integrate HighByte with Tiger Cloud](/docs/integrate/data-ingestion-streaming/highbyte/index.md): Connect operational technology sources, model the data, and stream it to your service
- [Integrate HiveMQ with Tiger Cloud](/docs/integrate/data-ingestion-streaming/hivemq/index.md): Connect HiveMQ to Tiger Cloud and stream MQTT messages into a hypertable
- [Integrate Ignition with Tiger Cloud](/docs/integrate/data-ingestion-streaming/ignition/index.md): Connect Ignition SCADA to Tiger Cloud and store tag history
- [Integrate Kepware KEPServerEX with Tiger Cloud](/docs/integrate/data-ingestion-streaming/kepware-kepserverex/index.md): Stream OPC tag data from Kepware DataLogger into Tiger Cloud and store it in a hypertable
- [Integrate Litmus Edge with Tiger Cloud](/docs/integrate/data-ingestion-streaming/litmus-edge/index.md): Stream industrial device data from Litmus Edge into your service using the PostgreSQL integration connector
- [Integrate Node-RED with Tiger Cloud](/docs/integrate/data-ingestion-streaming/node-red/index.md): Use Node-RED to stream events into Tiger Data and persist them in a hypertable.
- [Connect to Tiger Data](/docs/integrate/find-connection-details/index.md): Connect to Tiger Cloud, self-hosted TimescaleDB, or MST using any PostgreSQL client
- [Observability & alerting](/docs/integrate/observability-alerting/index.md): Use your monitoring and alerting tools with Tiger Data
- [Integrate Azure Monitor with Tiger Cloud](/docs/integrate/observability-alerting/azure-monitor/index.md): Export telemetry data to monitor and analyze your service performance and health with Azure Monitor
- [Integrate Amazon CloudWatch with Tiger Cloud](/docs/integrate/observability-alerting/cloudwatch/index.md): Export telemetry data to monitor and analyze your service performance and health
- [Integrate Datadog with Tiger Cloud](/docs/integrate/observability-alerting/datadog/index.md): Export telemetry data and collect metrics to monitor your service performance
- [Metrics exported by Tiger Cloud exporters](/docs/integrate/observability-alerting/exported-metrics/index.md): Reference for system and PostgreSQL metrics exported by Tiger Cloud
- [Integrate Grafana with Tiger Cloud](/docs/integrate/observability-alerting/grafana/index.md): Query, visualize, and explore your data with interactive dashboards
- [Integrate Prometheus with Tiger Cloud](/docs/integrate/observability-alerting/prometheus/index.md): Export telemetry metrics from your service to monitor system performance and health
- [Integrate Telegraf with Tiger Cloud](/docs/integrate/observability-alerting/telegraf/index.md): Ingest metrics and events from databases, systems, and IoT sensors
- [Query & administration](/docs/integrate/query-administration/index.md): Use your query and administration tools with Tiger Data
- [Integrate Azure Data Studio with Tiger Cloud](/docs/integrate/query-administration/azure-data-studio/index.md): Query and manage your database with a cross-platform data analytics tool
- [Integrate DBeaver with Tiger Cloud](/docs/integrate/query-administration/dbeaver/index.md): Manage and query your data with a cross-platform SQL editor and administration tool
- [Integrate pgAdmin with Tiger Cloud](/docs/integrate/query-administration/pgadmin/index.md): Query, visualize, and manage your database with an open-source administration tool
- [Integrate Postgres with Tiger Cloud](/docs/integrate/query-administration/postgresql/index.md): Query other Postgres data bases using foreign data wrappers
- [Connect to Tiger Cloud with psql](/docs/integrate/query-administration/psql/index.md): Connect to your Tiger Cloud service and run interactive queries with psql
- [Integrate qStudio with Tiger Cloud](/docs/integrate/query-administration/qstudio/index.md): Connect to your Tiger Cloud service and visualize your data with qStudio
- [Secure connectivity](/docs/integrate/secure-connectivity/index.md): Connect to Tiger Data with VPNs, tunnels, and secure access
- [Integrate Amazon Web Services with Tiger Cloud](/docs/integrate/secure-connectivity/aws/index.md): Connect your AWS infrastructure to Tiger Cloud using AWS Transit Gateway
- [Integrate your data center with Tiger Cloud](/docs/integrate/secure-connectivity/corporate-data-center/index.md): Connect your on-premise infrastructure to Tiger Cloud using AWS Transit Gateway
- [Integrate Google Cloud with Tiger Cloud](/docs/integrate/secure-connectivity/google-cloud/index.md): Connect your Google Cloud infrastructure to Tiger Cloud using AWS Transit Gateway
- [Integrate Microsoft Azure with Tiger Cloud](/docs/integrate/secure-connectivity/microsoft-azure/index.md): Connect your Azure infrastructure to Tiger Cloud on Azure using Azure Private Link
- [Troubleshoot](/docs/integrate/troubleshooting/index.md): Troubleshoot common problems that occur when integrating Tiger Cloud services with third-party solutions
- [Integrate](/docs/integrations/index.md): Integrate Tiger Cloud with third-party solutions to extend what you can do with your data
- [Component kitchen sink](/docs/kitchen-sink/index.md): Internal test page rendering every component and content element used in the docs, for visual and regression checks.
- [Get to know Tiger Data](/docs/learn/index.md): Concepts, comparisons, architecture, how features connect, and the glossary
- [Feature comparison](/docs/learn/capabilities-and-comparison/feature-comparison/index.md): Compare features across Tiger Cloud on AWS, Tiger Cloud on Azure, and self-hosted TimescaleDB
- [Understand capabilities](/docs/learn/capabilities-and-comparison/understand-capabilities/index.md): Learn how TimescaleDB and Tiger Cloud capabilities work together to power time-series and analytics workloads
- [Understand chunks](/docs/learn/chunks/understanding-chunks/index.md): What chunks are, why they matter for real-time analytics, and how to use them effectively
- [Compression methods in hypercore](/docs/learn/columnar-storage/compression-methods/index.md): Understand the compression algorithms used when converting data from the rowstore to the columnstore
- [Understand hypercore](/docs/learn/columnar-storage/understand-hypercore/index.md): How Tiger Data's hybrid row-columnar engine accelerates analytics while keeping ingest fast
- [Understand continuous aggregates](/docs/learn/continuous-aggregates/index.md): Learn how TimescaleDB continuous aggregates combine your data into analytic summaries and are refreshed in the background when new data is added
- [Hierarchical continuous aggregates](/docs/learn/continuous-aggregates/hierarchical-continuous-aggregates/index.md): Create continuous aggregates on top of continuous aggregates to summarize data at different levels of granularity
- [Materialized hypertables](/docs/learn/continuous-aggregates/materialized-hypertables/index.md): Continuous aggregates store aggregated data in materialized hypertables. Learn how to manage them
- [Real-time aggregates](/docs/learn/continuous-aggregates/real-time-aggregates/index.md): Real-time aggregates combine pre-aggregated data with the most recent raw data for up-to-date results
- [Time and continuous aggregates](/docs/learn/continuous-aggregates/time-and-continuous-aggregates/index.md): Learn to work with timezones and continuous aggregates
- [Understand the data lifecycle](/docs/learn/data-lifecycle/index.md): Learn how to manage time-series data from ingestion to deletion using hypertables, continuous aggregates, tiered storage, and retention policies
- [Understand data retention](/docs/learn/data-lifecycle/data-retention/about-data-retention/index.md): Discard old data as it reaches a certain age, manually or by setting up automated policies
- [About data retention with continuous aggregates](/docs/learn/data-lifecycle/data-retention/data-retention-with-continuous-aggregates/index.md): Combine continuous aggregates with data retention to save on raw data storage while keeping summarized data for historical analysis
- [Manually drop chunks](/docs/learn/data-lifecycle/data-retention/manually-drop-chunks/index.md): Manually drop chunks from your hypertables based on time value
- [Understand tiered storage](/docs/learn/data-lifecycle/storage/about-storage-tiers/index.md): Learn how Tiger Cloud helps you save on storage costs with a high-performance storage tier and a low-cost object storage tier
- [Understand time buckets](/docs/learn/data-lifecycle/time-buckets/about-time-buckets/index.md): Learn how time buckets help you aggregate data by time interval for efficient and simple real-time analytics
- [Use time buckets](/docs/learn/data-lifecycle/time-buckets/use-time-buckets/index.md): Group data by time interval using the time_bucket function to perform aggregate calculations over arbitrary time intervals
- [Understand the data lifecycle](/docs/learn/data-management/data-lifecycle/index.md): Learn how to manage time-series data from ingestion to deletion using hypertables, continuous aggregates, tiered storage, and retention policies
- [Design your data model](/docs/learn/data-model/design-your-data-model/index.md): Overview of the data model section covering table layouts, partition columns, keys, and schema optimization
- [Primary keys, time columns, and uniqueness for hypertables](/docs/learn/data-model/primary-keys-time-and-uniqueness/index.md): Choose a time partition column, primary keys, and unique constraints so your hypertable matches TimescaleDB rules and your query patterns
- [Understand schema optimization](/docs/learn/data-model/understand-database-schemas/index.md): Schema optimization options available in TimescaleDB and Tiger Cloud, including indexes, constraints, triggers, tablespaces, JSON, and FDW
- [Wide, narrow, and medium tables](/docs/learn/data-model/wide-narrow-medium-tables/index.md): Choose a narrow, wide, or medium table layout for your time-series data in PostgreSQL
- [Deep dive overview](/docs/learn/deep-dive/index.md): Advanced topics and architecture deep dives
- [Tiger Data architecture for real-time analytics](/docs/learn/deep-dive/whitepaper/index.md): A whitepaper detailing the architectural choices and optimizations for real-time analytics that power TimescaleDB and Tiger Cloud
- [Glossary](/docs/learn/glossary/index.md): Technical terms and concepts for Tiger Data products, TimescaleDB, and real-time analytics
- [About TimescaleDB hyperfunctions](/docs/learn/hyperfunctions/about-hyperfunctions/index.md): Use hyperfunctions for enhanced real-time analytics
- [Create and configure a hypertable](/docs/learn/hypertables/creating-and-configuring-hypertables/index.md): Create a hypertable, set chunk intervals, control default indexes, and migrate existing data
- [Hypertable indexes](/docs/learn/hypertables/hypertable-indexes/index.md): Default indexes, supported index types, and links to indexing guides for hypertables
- [Hypertable operations](/docs/learn/hypertables/optimize-data-in-hypertables/index.md): Create, alter, and drop a hypertable, and speed up data ingest with direct compress
- [Partition a hypertable](/docs/learn/hypertables/partitioning-hypertables/index.md): Partition a hypertable by time or integer columns, and understand when to use space partitioning
- [Size hypertable chunks](/docs/learn/hypertables/sizing-hypertable-chunks/index.md): Choose a chunk interval that balances memory usage, query planning, and columnstore effectiveness
- [Understand hypertables](/docs/learn/hypertables/understand-hypertables/index.md): Hypertables are PostgreSQL tables with special features that power real-time analytics on time-series and event data
- [Key vector concepts for pgvector](/docs/learn/search/key-vector-database-concepts-for-understanding-pgvector/index.md): Learn how pgvector stores embeddings in ordinary tables, how nearest-neighbor queries and distance operators work, and why approximate indexes matter on Tiger Cloud.
- [Understand pgvector and pgvectorscale](/docs/learn/search/pgvector-pgvectorsearch/index.md): Learn how vector embeddings power semantic search, how pgvector and pgvectorscale work together on Tiger Cloud, and where to read about indexes, pgai, and BM25 hybrid search.
- [Understand pg_textsearch and BM25 search](/docs/learn/search/using-pg-textsearch/index.md): Learn why BM25 full-text search matters, how pg_textsearch ranks results, and when to open the Tiger Cloud extension guide for setup and tuning.
- [Tiger CLI and Tiger MCP](/docs/learn/tiger-cli-mcp/index.md): Understand Tiger CLI and Tiger MCP, how they compare to the REST API, and where each fits in your workflow
- [Tiger Cloud](/docs/learn/tiger-cloud/index.md): Learn about Tiger Cloud, a fully managed cloud database service built on TimescaleDB and PostgreSQL for time-series and analytics workloads
- [Cloud-exclusive features](/docs/learn/tiger-cloud/cloud-exclusive-features/index.md): Learn about the features and capabilities available exclusively in Tiger Cloud
- [Tiger Cloud essentials](/docs/learn/tiger-cloud/tiger-cloud-essentials/index.md): Technical walkthrough covering hypertables, hypercore, continuous aggregates, and tiered storage in a single workflow
- [Data](/docs/manage-data/index.md): Postgres for time-series, real-time analytics and events
- [Migrate to Tiger Cloud](/docs/migrate/index.md): Move your data to Tiger Cloud from other databases
- [Choose a migration approach](/docs/migrate/choose-your-approach/index.md): Compare the tools for moving data to Tiger Cloud and pick the right approach for your source database, size, and downtime budget
- [Dual-write and backfill](/docs/migrate/dual-write-and-backfill/index.md): Migrate a hypertable or your entire database to Tiger Cloud with low downtime using dual-write and backfill
- [Migrate from non-PostgreSQL using dual-write and backfill](/docs/migrate/dual-write-and-backfill/dual-write-from-other/index.md): Migrate from a non-PostgreSQL database to Tiger Cloud using the low-downtime dual-write and backfill method
- [Migrate from PostgreSQL using dual-write and backfill](/docs/migrate/dual-write-and-backfill/dual-write-from-postgres/index.md): Migrate from a PostgreSQL database to Tiger Cloud using the low-downtime dual-write and backfill method
- [Migrate from TimescaleDB using dual-write and backfill](/docs/migrate/dual-write-and-backfill/dual-write-from-timescaledb/index.md): Migrate from a TimescaleDB database to Tiger Cloud using the low-downtime dual-write and backfill method
- [Migrate with timescaledb-backfill](/docs/migrate/dual-write-and-backfill/timescaledb-backfill/index.md): Use the timescaledb-backfill tool to migrate your database to Tiger Cloud by copying historic data into your service
- [Upload a file using Tiger Console](/docs/migrate/import-console/index.md): Upload CSV, Parquet, and text files into your Tiger Cloud service using Tiger Console. Drag and drop from your local machine, or provide a path to the file in S3
- [Upload a file using the terminal](/docs/migrate/import-terminal/index.md): Upload CSV, MySQL, and Parquet files from your machine using the terminal
- [Stream data from Kafka](/docs/migrate/livesync-for-kafka/index.md): Stream data from Kafka into a Tiger Cloud service to store, query, and analyze your Kafka events efficiently
- [Sync data from PostgreSQL](/docs/migrate/livesync-for-postgresql/index.md): Sync PostgreSQL tables to Tiger Cloud in real time using the source PostgreSQL connector
- [Sync data from S3](/docs/migrate/livesync-for-s3/index.md): Sync CSV and Parquet files from an S3 bucket to Tiger Cloud in real time using the source S3 connector
- [Livesync replication](/docs/migrate/livesync-replication/index.md): Migrate your entire PostgreSQL or TimescaleDB database to Tiger Cloud with near-zero downtime using Livesync
- [Livesync replication advanced topics](/docs/migrate/livesync-replication-advanced/index.md): Advanced Livesync replication scenarios for migrating to Tiger Cloud
- [Livesync replication troubleshooting](/docs/migrate/livesync-replication-troubleshooting/index.md): Troubleshoot Livesync replication when migrating to Tiger Cloud
- [Migrate with downtime](/docs/migrate/migrate-with-downtime/index.md): Migrate a hypertable or an entire database to Tiger Cloud with native PostgreSQL commands using pg_dump and pg_restore
- [FAQ and troubleshooting](/docs/migrate/troubleshooting/index.md): Troubleshooting known issues in database migrations to Tiger Cloud
- [Reference](/docs/reference/index.md): SQL function reference, analytics functions, configuration, and the tools and APIs for managing Tiger Cloud
- [Configuration reference](/docs/reference/configuration/index.md): PostgreSQL and TimescaleDB configuration settings
- [Tiger Cloud API reference](/docs/reference/tiger-cloud/index.md): API reference for Tiger Cloud, including data tiering SQL functions and the Tiger Cloud REST API for managing services programmatically
- [Tiger Cloud REST API (local preview)](/docs/reference/tiger-cloud-rest-local-preview/index.md): Generated REST reference is disabled in this build
- [Data tiering overview](/docs/reference/tiger-cloud/data-tiering/index.md): Tiger Cloud API reference for data tiering. Includes SQL functions for moving older chunks to object storage on a schedule that you define
- [add_tiering_policy()](/docs/reference/tiger-cloud/data-tiering/add_tiering_policy/index.md): Add a policy to automatically tier older chunks to object storage
- [disable_tiering()](/docs/reference/tiger-cloud/data-tiering/disable_tiering/index.md): Disable tiering on a hypertable and remove its object storage catalog entries
- [remove_tiering_policy()](/docs/reference/tiger-cloud/data-tiering/remove_tiering_policy/index.md): Remove the tiering policy from a hypertable or continuous aggregate
- [tier_chunk()](/docs/reference/tiger-cloud/data-tiering/tier_chunk/index.md): Manually tier an individual chunk to object storage
- [untier_chunk()](/docs/reference/tiger-cloud/data-tiering/untier_chunk/index.md): Move a tiered chunk from object storage back to local storage
- [Tiger CLI reference](/docs/reference/tiger-cloud/tiger-cli/index.md): Command reference for Tiger CLI, including every command, configuration parameter, and global flag for managing Tiger Cloud
- [Tiger MCP reference](/docs/reference/tiger-cloud/tiger-mcp/index.md): Tool reference for Tiger MCP, the Model Context Protocol server bundled with Tiger CLI
- [TimescaleDB API reference](/docs/reference/timescaledb/index.md): Complete API reference for TimescaleDB functions, SQL commands, and time-series data management
- [Administrative functions](/docs/reference/timescaledb/administration/index.md): Administration functions help you manage your service before and after recovery, as well as keeping track of your data
- [get_telemetry_report()](/docs/reference/timescaledb/administration/get_telemetry_report/index.md): View the background telemetry string sent to Timescale
- [timescaledb_post_restore()](/docs/reference/timescaledb/administration/timescaledb_post_restore/index.md): Perform required operations after finishing a database restore
- [timescaledb_pre_restore()](/docs/reference/timescaledb/administration/timescaledb_pre_restore/index.md): Prepare the database for a restore operation
- [Service configuration](/docs/reference/timescaledb/configuration/index.md): Use the default PostgreSQL server configuration settings for your Tiger Cloud service, or customize them as needed
- [Grand Unified Configuration (GUC) parameters](/docs/reference/timescaledb/configuration/gucs/index.md): Optimize the behavior of TimescaleDB using Grand Unified Configuration (GUC) parameters
- [Configuration parameters](/docs/reference/timescaledb/configuration/tiger-postgres/index.md): Configure your TimescaleDB instance including settings related to memory, workers, disk writes, and transactional locks
- [Continuous aggregates overview](/docs/reference/timescaledb/continuous-aggregates/index.md): TimescaleDB reference for calculating continuous aggregates on your data. Includes SQL functions and views related to creating, altering, and dropping continuous aggregates
- [add_continuous_aggregate_policy()](/docs/reference/timescaledb/continuous-aggregates/add_continuous_aggregate_policy/index.md): Add policy to schedule automatic refresh of a continuous aggregate
- [add_policies()](/docs/reference/timescaledb/continuous-aggregates/add_policies/index.md): Add refresh, compression, and data retention policies on a continuous aggregate
- [ALTER MATERIALIZED VIEW (continuous aggregate)](/docs/reference/timescaledb/continuous-aggregates/alter_materialized_view/index.md): Change an existing continuous aggregate
- [alter_policies()](/docs/reference/timescaledb/continuous-aggregates/alter_policies/index.md): Alter refresh, compression, or data retention policies on a continuous aggregate
- [cagg_migrate()](/docs/reference/timescaledb/continuous-aggregates/cagg_migrate/index.md): Migrate a continuous aggregate from the old format to the new format introduced in TimescaleDB 2.7
- [CREATE MATERIALIZED VIEW (continuous aggregate)](/docs/reference/timescaledb/continuous-aggregates/create_materialized_view/index.md): Create a continuous aggregate on a hypertable or another continuous aggregate
- [DROP MATERIALIZED VIEW (continuous aggregate)](/docs/reference/timescaledb/continuous-aggregates/drop_materialized_view/index.md): Drop a continuous aggregate view
- [refresh_continuous_aggregate()](/docs/reference/timescaledb/continuous-aggregates/refresh_continuous_aggregate/index.md): Manually refresh a continuous aggregate
- [remove_all_policies()](/docs/reference/timescaledb/continuous-aggregates/remove_all_policies/index.md): Remove all policies from a continuous aggregate
- [remove_continuous_aggregate_policy()](/docs/reference/timescaledb/continuous-aggregates/remove_continuous_aggregate_policy/index.md): Remove a refresh policy from a continuous aggregate
- [remove_policies()](/docs/reference/timescaledb/continuous-aggregates/remove_policies/index.md): Remove refresh, compression, or data retention policies from a continuous aggregate
- [show_policies()](/docs/reference/timescaledb/continuous-aggregates/show_policies/index.md): Show all policies that are currently set on a continuous aggregate
- [Data retention overview](/docs/reference/timescaledb/data-retention/index.md): TimescaleDB API reference for data retention. Includes SQL functions for adding and removing data retention policies that run on a schedule that you define
- [add_retention_policy()](/docs/reference/timescaledb/data-retention/add_retention_policy/index.md): Add a policy to drop older chunks
- [remove_retention_policy()](/docs/reference/timescaledb/data-retention/remove_retention_policy/index.md): Remove a retention policy from a hypertable
- [Hypercore](/docs/reference/timescaledb/hypercore/index.md): Reference information about the TimescaleDB hybrid row-columnar storage engine
- [add_columnstore_policy()](/docs/reference/timescaledb/hypercore/add_columnstore_policy/index.md): Set a policy to automatically move chunks in a hypertable to the columnstore when they reach a given age.
- [add_compaction_policy()](/docs/reference/timescaledb/hypercore/add_compaction_policy/index.md): Set a policy to automatically compact unordered chunks in the columnstore
- [ALTER TABLE (hypercore)](/docs/reference/timescaledb/hypercore/alter_table/index.md): Enable the columnstore for a hypertable.
- [timescaledb_information.chunk_columnstore_settings](/docs/reference/timescaledb/hypercore/chunk_columnstore_settings/index.md): Get information about settings on each chunk in the columnstore
- [chunk_columnstore_stats()](/docs/reference/timescaledb/hypercore/chunk_columnstore_stats/index.md): Get statistics about chunks in the columnstore
- [convert_to_columnstore()](/docs/reference/timescaledb/hypercore/convert_to_columnstore/index.md): Manually add a chunk to the columnstore
- [convert_to_rowstore()](/docs/reference/timescaledb/hypercore/convert_to_rowstore/index.md): Move a chunk from the columnstore to the rowstore
- [timescaledb_information.hypertable_columnstore_settings](/docs/reference/timescaledb/hypercore/hypertable_columnstore_settings/index.md): Get information about columnstore settings for all hypertables
- [hypertable_columnstore_stats()](/docs/reference/timescaledb/hypercore/hypertable_columnstore_stats/index.md): Get columnstore statistics related to the columnstore
- [remove_columnstore_policy()](/docs/reference/timescaledb/hypercore/remove_columnstore_policy/index.md): Remove a columnstore policy from a hypertable
- [remove_compaction_policy()](/docs/reference/timescaledb/hypercore/remove_compaction_policy/index.md): Remove a compaction policy from a hypertable
- [Hyperfunctions overview](/docs/reference/timescaledb/hyperfunctions/index.md): Functions that enable you to analyze time-series data efficiently. These functions provide essential capabilities for time bucketing, data distribution analysis, and gapfilling.
- [Distribution analysis overview](/docs/reference/timescaledb/hyperfunctions/distribution-analysis/index.md): Functions for analyzing data distribution with histograms and approximate row counts
- [approximate_row_count()](/docs/reference/timescaledb/hyperfunctions/distribution-analysis/approximate_row_count/index.md): Estimate the number of rows in a table
- [histogram()](/docs/reference/timescaledb/hyperfunctions/distribution-analysis/histogram/index.md): Partition the dataset into buckets and get the number of counts in each bucket
- [Gapfilling overview](/docs/reference/timescaledb/hyperfunctions/time_bucket_gapfill/index.md): Aggregate data by time interval while filling in gaps of missing data
- [interpolate()](/docs/reference/timescaledb/hyperfunctions/time_bucket_gapfill/interpolate/index.md): Fill in missing values by linear interpolation
- [locf()](/docs/reference/timescaledb/hyperfunctions/time_bucket_gapfill/locf/index.md): Fill in missing values by carrying the last observed value forward
- [time_bucket_gapfill()](/docs/reference/timescaledb/hyperfunctions/time_bucket_gapfill/time_bucket_gapfill/index.md): Bucket rows by time interval while filling gaps in data
- [Time series utilities overview](/docs/reference/timescaledb/hyperfunctions/time-series-utilities/index.md): Functions for time bucketing, ordered selection, and time-based calculations
- [days_in_month()](/docs/reference/timescaledb/hyperfunctions/time-series-utilities/days_in_month/index.md): Calculates days in month given a timestamptz
- [first()](/docs/reference/timescaledb/hyperfunctions/time-series-utilities/first/index.md): Get the first value in one column when rows are ordered by another column
- [last()](/docs/reference/timescaledb/hyperfunctions/time-series-utilities/last/index.md): Get the last value in one column when rows are ordered by another column
- [month_normalize()](/docs/reference/timescaledb/hyperfunctions/time-series-utilities/month_normalize/index.md): Normalize a monthly metric based on number of days in month
- [time_bucket()](/docs/reference/timescaledb/hyperfunctions/time-series-utilities/time_bucket/index.md): Bucket rows by time interval to calculate aggregates
- [to_epoch()](/docs/reference/timescaledb/hyperfunctions/time-series-utilities/to_epoch/index.md): Convert a timestamptz to a Unix epoch time
- [Hypertables and chunks](/docs/reference/timescaledb/hypertables/index.md): SQL commands and functions for creating and managing hypertables and chunks
- [add_dimension()](/docs/reference/timescaledb/hypertables/add_dimension/index.md): Add a space-partitioning dimension to a hypertable
- [add_dimension() (deprecated)](/docs/reference/timescaledb/hypertables/add_dimension_old/index.md): Add a space-partitioning dimension to a hypertable
- [add_reorder_policy()](/docs/reference/timescaledb/hypertables/add_reorder_policy/index.md): Add a policy to reorder rows in hypertable chunks
- [attach_chunk()](/docs/reference/timescaledb/hypertables/attach_chunk/index.md): Attach a chunk to a hypertable
- [attach_tablespace()](/docs/reference/timescaledb/hypertables/attach_tablespace/index.md): Attach a tablespace to a hypertable
- [chunk_rewrite_cleanup()](/docs/reference/timescaledb/hypertables/chunk_rewrite_cleanup/index.md): Clean up state from an aborted chunk rewrite operation
- [chunks_detailed_size()](/docs/reference/timescaledb/hypertables/chunks_detailed_size/index.md): Get detailed information about disk space used by chunks
- [create_chunk()](/docs/reference/timescaledb/hypertables/create_chunk/index.md): Create a chunk with specified dimensional constraints
- [create_hypertable()](/docs/reference/timescaledb/hypertables/create_hypertable/index.md): Create a hypertable
- [create_hypertable() (old interface)](/docs/reference/timescaledb/hypertables/create_hypertable_old/index.md): Create a hypertable
- [CREATE INDEX (transaction per chunk)](/docs/reference/timescaledb/hypertables/create_index/index.md): Create a hypertable index using a separate transaction for each chunk
- [CREATE TABLE](/docs/reference/timescaledb/hypertables/create_table/index.md): Create a table or a hypertable
- [detach_chunk()](/docs/reference/timescaledb/hypertables/detach_chunk/index.md): Detach a chunk from a hypertable.
- [detach_tablespace()](/docs/reference/timescaledb/hypertables/detach_tablespace/index.md): Detach a tablespace from a hypertable
- [detach_tablespaces()](/docs/reference/timescaledb/hypertables/detach_tablespaces/index.md): Detach all tablespaces from a hypertable
- [disable_chunk_skipping()](/docs/reference/timescaledb/hypertables/disable_chunk_skipping/index.md): Disable range tracking for columns of chunks from a hypertable
- [drop_chunk()](/docs/reference/timescaledb/hypertables/drop_chunk/index.md): Drop a single chunk
- [drop_chunks()](/docs/reference/timescaledb/hypertables/drop_chunks/index.md): Delete chunks by time range
- [enable_chunk_skipping()](/docs/reference/timescaledb/hypertables/enable_chunk_skipping/index.md): Enable range tracking for columns of chunks from a hypertable
- [hypertable_approximate_detailed_size()](/docs/reference/timescaledb/hypertables/hypertable_approximate_detailed_size/index.md): Get detailed information about approximate disk space used by a hypertable
- [hypertable_approximate_size()](/docs/reference/timescaledb/hypertables/hypertable_approximate_size/index.md): Get the approximate total disk space used by a hypertable
- [hypertable_detailed_size()](/docs/reference/timescaledb/hypertables/hypertable_detailed_size/index.md): Get detailed information about disk space used by a hypertable
- [hypertable_index_size()](/docs/reference/timescaledb/hypertables/hypertable_index_size/index.md): Get the disk space used by a hypertable index
- [hypertable_size()](/docs/reference/timescaledb/hypertables/hypertable_size/index.md): Get the total disk space used by a hypertable
- [merge_chunks()](/docs/reference/timescaledb/hypertables/merge_chunks/index.md): Merge two or more chunks into one chunk
- [merge_chunks_concurrently()](/docs/reference/timescaledb/hypertables/merge_chunks_concurrently/index.md): Merge two or more chunks into one chunk without blocking reads
- [move_chunk()](/docs/reference/timescaledb/hypertables/move_chunk/index.md): Move a chunk and its indexes to a different tablespace
- [remove_reorder_policy()](/docs/reference/timescaledb/hypertables/remove_reorder_policy/index.md): Remove a reorder policy from a hypertable
- [reorder_chunk()](/docs/reference/timescaledb/hypertables/reorder_chunk/index.md): Reorder rows in a chunk
- [set_chunk_time_interval()](/docs/reference/timescaledb/hypertables/set_chunk_time_interval/index.md): Change the chunk time interval of a hypertable
- [set_integer_now_func()](/docs/reference/timescaledb/hypertables/set_integer_now_func/index.md): Define the relationship between integer time values and actual time
- [show_chunks()](/docs/reference/timescaledb/hypertables/show_chunks/index.md): Show the chunks belonging to a hypertable
- [show_tablespaces()](/docs/reference/timescaledb/hypertables/show_tablespaces/index.md): Show the tablespaces attached to a hypertable
- [split_chunk()](/docs/reference/timescaledb/hypertables/split_chunk/index.md): Split a large chunk at a specific point in time.
- [Informational views overview](/docs/reference/timescaledb/informational-views/index.md): The full list of informational views available in TimescaleDB. Informational views provide detailed information about the state of your data, hypertables, chunks, and any jobs or policies you have in place
- [timescaledb_information.chunk_columnstore_settings](/docs/reference/timescaledb/informational-views/chunk_columnstore_settings/index.md): Get information about settings on each chunk in the columnstore
- [timescaledb_information.chunks](/docs/reference/timescaledb/informational-views/chunks/index.md): Get metadata about hypertable chunks
- [timescaledb_information.continuous_aggregates](/docs/reference/timescaledb/informational-views/continuous_aggregates/index.md): Get metadata and settings information for continuous aggregates
- [timescaledb_information.dimensions](/docs/reference/timescaledb/informational-views/dimensions/index.md): Get information on the dimensions of hypertables
- [timescaledb_information.hypertable_columnstore_settings](/docs/reference/timescaledb/informational-views/hypertable_columnstore_settings/index.md): Get information about columnstore settings for all hypertables
- [timescaledb_information.hypertables](/docs/reference/timescaledb/informational-views/hypertables/index.md): Get metadata about hypertables
- [timescaledb_information.job_errors](/docs/reference/timescaledb/informational-views/job_errors/index.md): Get information about background job errors
- [timescaledb_information.job_history](/docs/reference/timescaledb/informational-views/job_history/index.md): Get information about background job execution
- [timescaledb_information.job_stats](/docs/reference/timescaledb/informational-views/job_stats/index.md): Get information and statistics about automatically run jobs
- [timescaledb_information.jobs](/docs/reference/timescaledb/informational-views/jobs/index.md): Get information about all jobs registered with the automatic scheduler
- [timescaledb_experimental.policies](/docs/reference/timescaledb/informational-views/policies/index.md): Get information about all policies set on continuous aggregates
- [Jobs and automation overview](/docs/reference/timescaledb/jobs-automation/index.md): TimescaleDB API reference for jobs. Includes SQL functions for adding, altering, deleting, and running a job
- [add_job()](/docs/reference/timescaledb/jobs-automation/add_job/index.md): Add a job to run a function or procedure automatically
- [alter_job()](/docs/reference/timescaledb/jobs-automation/alter_job/index.md): Alter a job that is scheduled to run automatically
- [delete_job()](/docs/reference/timescaledb/jobs-automation/delete_job/index.md): Delete a job from the automatic scheduler
- [run_job()](/docs/reference/timescaledb/jobs-automation/run_job/index.md): Manually run a job
- [API reference tag overview](/docs/reference/timescaledb/tag-overview/index.md): The TimescaleDB API reference includes tags to categorize the available SQL functions and views
- [UUIDv7 functions](/docs/reference/timescaledb/uuid-functions/index.md): Create a hypertable partitioned by time-based UUIDv7
- [generate_uuidv7()](/docs/reference/timescaledb/uuid-functions/generate_uuidv7/index.md): Generate a version 7 UUID based on current time
- [to_uuidv7()](/docs/reference/timescaledb/uuid-functions/to_uuidv7/index.md): Create a version 7 UUID from a Postgres timestamp
- [to_uuidv7_boundary()](/docs/reference/timescaledb/uuid-functions/to_uuidv7_boundary/index.md): Create a version 7 "boundary" UUID from a Postgres timestamp
- [uuid_timestamp()](/docs/reference/timescaledb/uuid-functions/uuid_timestamp/index.md): Extract a Postgres timestamp from a version 7 UUID
- [uuid_timestamp_micros()](/docs/reference/timescaledb/uuid-functions/uuid_timestamp_micros/index.md): Extract a Postgres timestamp with microsecond precision from a version 7 UUID
- [uuid_version()](/docs/reference/timescaledb/uuid-functions/uuid_version/index.md): Extract the version of a UUID
- [TimescaleDB Toolkit API reference](/docs/reference/toolkit/index.md): Analyze anything you have stored as time-series data, including IoT devices, IT systems, marketing analytics, user behavior, financial metrics, and cryptocurrency.
- [Approximate count distinct overview](/docs/reference/toolkit/approximate-count-distinct/index.md): Estimate the number of distinct values in a dataset, also known as cardinality estimation
- [approx_count_distinct()](/docs/reference/toolkit/approximate-count-distinct/approx_count_distinct/index.md): Aggregate data into a hyperloglog for approximate counting without specifying the number of buckets
- [distinct_count()](/docs/reference/toolkit/approximate-count-distinct/distinct_count/index.md): Estimate the number of distinct values from a hyperloglog
- [hyperloglog()](/docs/reference/toolkit/approximate-count-distinct/hyperloglog/index.md): Aggregate data into a hyperloglog for approximate counting
- [rollup()](/docs/reference/toolkit/approximate-count-distinct/rollup/index.md): Roll up multiple hyperloglogs
- [stderror()](/docs/reference/toolkit/approximate-count-distinct/stderror/index.md): Estimate the relative standard error of a hyperloglog
- [Financial analysis overview](/docs/reference/toolkit/candlestick_agg/index.md): Perform analysis of financial asset data
- [candlestick()](/docs/reference/toolkit/candlestick_agg/candlestick/index.md): Transform pre-aggregated candlestick data into the correct form to use with `candlestick_agg` functions
- [candlestick_agg()](/docs/reference/toolkit/candlestick_agg/candlestick_agg/index.md): Aggregate tick data into an intermediate form for further calculation
- [close()](/docs/reference/toolkit/candlestick_agg/close/index.md): Get the closing price from a candlestick aggregate
- [close_time()](/docs/reference/toolkit/candlestick_agg/close_time/index.md): Get the timestamp corresponding to the closing time from a candlestick aggregate
- [high()](/docs/reference/toolkit/candlestick_agg/high/index.md): Get the high price from a candlestick aggregate
- [high_time()](/docs/reference/toolkit/candlestick_agg/high_time/index.md): Get the timestamp corresponding to the high time from a candlestick aggregate
- [low()](/docs/reference/toolkit/candlestick_agg/low/index.md): Get the low price from a candlestick aggregate
- [low_time()](/docs/reference/toolkit/candlestick_agg/low_time/index.md): Get the timestamp corresponding to the low time from a candlestick aggregate
- [open()](/docs/reference/toolkit/candlestick_agg/open/index.md): Get the opening price from a candlestick aggregate
- [open_time()](/docs/reference/toolkit/candlestick_agg/open_time/index.md): Get the timestamp corresponding to the open time from a candlestick aggregate
- [rollup()](/docs/reference/toolkit/candlestick_agg/rollup/index.md): Roll up multiple Candlestick aggregates
- [volume()](/docs/reference/toolkit/candlestick_agg/volume/index.md): Get the total volume from a candlestick aggregate
- [vwap()](/docs/reference/toolkit/candlestick_agg/vwap/index.md): Get the Volume Weighted Average Price from a candlestick aggregate
- [Counters and gauges overview](/docs/reference/toolkit/counters-and-gauges/index.md): Functions for analyzing monotonic counters and gauge metrics
- [Counter aggregation overview](/docs/reference/toolkit/counters-and-gauges/counter_agg/index.md): Functions for analyzing monotonically increasing counter metrics
- [corr()](/docs/reference/toolkit/counters-and-gauges/counter_agg/corr/index.md): Calculate the correlation coefficient from a counter aggregate
- [counter_agg()](/docs/reference/toolkit/counters-and-gauges/counter_agg/counter_agg/index.md): Aggregate counter data into an intermediate form for further analysis
- [counter_zero_time()](/docs/reference/toolkit/counters-and-gauges/counter_agg/counter_zero_time/index.md): Calculate the time when the counter value is predicted to have been zero
- [delta()](/docs/reference/toolkit/counters-and-gauges/counter_agg/delta/index.md): Calculate the change in a counter from a counter aggregate
- [extrapolated_delta()](/docs/reference/toolkit/counters-and-gauges/counter_agg/extrapolated_delta/index.md): Calculate the extrapolated change from a counter aggregate
- [extrapolated_rate()](/docs/reference/toolkit/counters-and-gauges/counter_agg/extrapolated_rate/index.md): Calculate the extrapolated rate of change from a counter aggregate
- [first_time()](/docs/reference/toolkit/counters-and-gauges/counter_agg/first_time/index.md): Get the first timestamp from a counter aggregate
- [first_val()](/docs/reference/toolkit/counters-and-gauges/counter_agg/first_val/index.md): Get the first value from a counter aggregate
- [idelta_left()](/docs/reference/toolkit/counters-and-gauges/counter_agg/idelta_left/index.md): Calculate the instantaneous change at the left, or earliest, edge of a counter aggregate
- [idelta_right()](/docs/reference/toolkit/counters-and-gauges/counter_agg/idelta_right/index.md): Calculate the instantaneous change at the right, or latest, edge of a counter aggregate
- [intercept()](/docs/reference/toolkit/counters-and-gauges/counter_agg/intercept/index.md): Calculate the y-intercept from a counter aggregate
- [interpolated_delta()](/docs/reference/toolkit/counters-and-gauges/counter_agg/interpolated_delta/index.md): Calculate the change in a counter, interpolating values at boundaries as needed
- [interpolated_rate()](/docs/reference/toolkit/counters-and-gauges/counter_agg/interpolated_rate/index.md): Calculate the rate of change in a counter, interpolating values at boundaries as needed
- [irate_left()](/docs/reference/toolkit/counters-and-gauges/counter_agg/irate_left/index.md): Calculate the instantaneous rate of change at the left, or earliest, edge of a counter aggregate
- [irate_right()](/docs/reference/toolkit/counters-and-gauges/counter_agg/irate_right/index.md): Calculate the instantaneous rate of change at the right, or latest, edge of a counter aggregate
- [last_time()](/docs/reference/toolkit/counters-and-gauges/counter_agg/last_time/index.md): Get the last timestamp from a counter aggregate
- [last_val()](/docs/reference/toolkit/counters-and-gauges/counter_agg/last_val/index.md): Get the last value from a counter aggregate
- [num_changes()](/docs/reference/toolkit/counters-and-gauges/counter_agg/num_changes/index.md): Get the number of times a counter changed from a counter aggregate
- [num_elements()](/docs/reference/toolkit/counters-and-gauges/counter_agg/num_elements/index.md): Get the number of points with distinct timestamps from a counter aggregate
- [num_resets()](/docs/reference/toolkit/counters-and-gauges/counter_agg/num_resets/index.md): Get the number of counter resets from a counter aggregate
- [rate()](/docs/reference/toolkit/counters-and-gauges/counter_agg/rate/index.md): Calculate the rate of change from a counter aggregate
- [rollup()](/docs/reference/toolkit/counters-and-gauges/counter_agg/rollup/index.md): Combine multiple counter aggregates
- [slope()](/docs/reference/toolkit/counters-and-gauges/counter_agg/slope/index.md): Calculate the slope from a counter aggregate
- [time_delta()](/docs/reference/toolkit/counters-and-gauges/counter_agg/time_delta/index.md): Calculate the difference between the first and last times from a counter aggregate
- [with_bounds()](/docs/reference/toolkit/counters-and-gauges/counter_agg/with_bounds/index.md): Add bounds to a counter aggregate
- [Gauge aggregation overview](/docs/reference/toolkit/counters-and-gauges/gauge_agg/index.md): Functions for analyzing gauge metrics that can increase or decrease
- [corr()](/docs/reference/toolkit/counters-and-gauges/gauge_agg/corr/index.md): Calculate the correlation coefficient from a gauge aggregate
- [delta()](/docs/reference/toolkit/counters-and-gauges/gauge_agg/delta/index.md): Calculate the change in a gauge from a gauge aggregate
- [extrapolated_delta()](/docs/reference/toolkit/counters-and-gauges/gauge_agg/extrapolated_delta/index.md): Calculate the extrapolated change from a gauge aggregate
- [extrapolated_rate()](/docs/reference/toolkit/counters-and-gauges/gauge_agg/extrapolated_rate/index.md): Calculate the extrapolated rate of change from a gauge aggregate
- [gauge_agg()](/docs/reference/toolkit/counters-and-gauges/gauge_agg/gauge_agg/index.md): Aggregate gauge data into an intermediate form for further analysis
- [gauge_zero_time()](/docs/reference/toolkit/counters-and-gauges/gauge_agg/gauge_zero_time/index.md): Calculate the time when the gauge value is predicted to have been zero
- [idelta_left()](/docs/reference/toolkit/counters-and-gauges/gauge_agg/idelta_left/index.md): Calculate the instantaneous change at the left, or earliest, edge of a gauge aggregate
- [idelta_right()](/docs/reference/toolkit/counters-and-gauges/gauge_agg/idelta_right/index.md): Calculate the instantaneous change at the right, or latest, edge of a gauge aggregate
- [intercept()](/docs/reference/toolkit/counters-and-gauges/gauge_agg/intercept/index.md): Calculate the y-intercept from a gauge aggregate
- [interpolated_delta()](/docs/reference/toolkit/counters-and-gauges/gauge_agg/interpolated_delta/index.md): Calculate the change in a gauge, interpolating values at boundaries as needed
- [interpolated_rate()](/docs/reference/toolkit/counters-and-gauges/gauge_agg/interpolated_rate/index.md): Calculate the rate of change in a gauge, interpolating values at boundaries as needed
- [irate_left()](/docs/reference/toolkit/counters-and-gauges/gauge_agg/irate_left/index.md): Calculate the instantaneous rate of change at the left, or earliest, edge of a gauge aggregate
- [irate_right()](/docs/reference/toolkit/counters-and-gauges/gauge_agg/irate_right/index.md): Calculate the instantaneous rate of change at the right, or latest, edge of a gauge aggregate
- [num_changes()](/docs/reference/toolkit/counters-and-gauges/gauge_agg/num_changes/index.md): Get the number of times a gauge changed from a gauge aggregate
- [num_elements()](/docs/reference/toolkit/counters-and-gauges/gauge_agg/num_elements/index.md): Get the number of points with distinct timestamps from a gauge aggregate
- [rate()](/docs/reference/toolkit/counters-and-gauges/gauge_agg/rate/index.md): Calculate the rate of change from a gauge aggregate
- [rollup()](/docs/reference/toolkit/counters-and-gauges/gauge_agg/rollup/index.md): Combine multiple gauge aggregates
- [slope()](/docs/reference/toolkit/counters-and-gauges/gauge_agg/slope/index.md): Calculate the slope from a gauge aggregate
- [time_delta()](/docs/reference/toolkit/counters-and-gauges/gauge_agg/time_delta/index.md): Calculate the difference between the first and last times from a gauge aggregate
- [with_bounds()](/docs/reference/toolkit/counters-and-gauges/gauge_agg/with_bounds/index.md): Add bounds to a gauge aggregate
- [Downsampling overview](/docs/reference/toolkit/downsampling/index.md): Functions for downsampling time-series data to visualize trends while preserving visual similarity
- [asap_smooth()](/docs/reference/toolkit/downsampling/asap_smooth/index.md): Downsample a time series using the ASAP smoothing algorithm
- [gp_lttb()](/docs/reference/toolkit/downsampling/gp_lttb/index.md): Downsample a time series using the Largest Triangle Three Buckets method, while preserving gaps in original data
- [lttb()](/docs/reference/toolkit/downsampling/lttb/index.md): Downsample a time series using the Largest Triangle Three Buckets method
- [Frequency analysis overview](/docs/reference/toolkit/frequency-analysis/index.md): Functions for analyzing the frequency of values in time-series data
- [Count-min sketch overview](/docs/reference/toolkit/frequency-analysis/count_min_sketch/index.md): Functions for estimating value counts using the count-min sketch data structure
- [approx_count()](/docs/reference/toolkit/frequency-analysis/count_min_sketch/approx_count/index.md): Estimate the number of times a value appears from a `CountMinSketch`
- [count_min_sketch()](/docs/reference/toolkit/frequency-analysis/count_min_sketch/count_min_sketch/index.md): Aggregate data into a `CountMinSketch` for approximate counting
- [Frequency aggregation overview](/docs/reference/toolkit/frequency-analysis/freq_agg/index.md): Functions for finding the most common values using the SpaceSaving algorithm
- [freq_agg()](/docs/reference/toolkit/frequency-analysis/freq_agg/freq_agg/index.md): Aggregate data into a space-saving aggregate for further frequency analysis
- [into_values()](/docs/reference/toolkit/frequency-analysis/freq_agg/into_values/index.md): Get a table of all frequency estimates from a space-saving aggregate
- [max_frequency()](/docs/reference/toolkit/frequency-analysis/freq_agg/max_frequency/index.md): Get the maximum bound of the estimated frequency for a given value in a space-saving aggregate
- [mcv_agg()](/docs/reference/toolkit/frequency-analysis/freq_agg/mcv_agg/index.md): Aggregate data into a space-saving aggregate for further calculation of most-frequent values
- [min_frequency()](/docs/reference/toolkit/frequency-analysis/freq_agg/min_frequency/index.md): Get the minimum bound of the estimated frequency for a given value in a space-saving aggregate
- [rollup()](/docs/reference/toolkit/frequency-analysis/freq_agg/rollup/index.md): Combine multiple frequency aggregates
- [topn()](/docs/reference/toolkit/frequency-analysis/freq_agg/topn/index.md): Get the top N most common values from a space-saving aggregate
- [Minimum and maximum overview](/docs/reference/toolkit/minimum-and-maximum/index.md): Find the smallest and largest values in a dataset
- [Maximum values overview](/docs/reference/toolkit/minimum-and-maximum/max_n/index.md): Get the N largest values from a column
- [Maximum values by overview](/docs/reference/toolkit/minimum-and-maximum/max_n_by/index.md): Get the N largest values with accompanying data
- [into_values()](/docs/reference/toolkit/minimum-and-maximum/max_n_by/into_values/index.md): Returns the highest values and associated data from a MaxNBy aggregate
- [max_n_by()](/docs/reference/toolkit/minimum-and-maximum/max_n_by/max_n_by/index.md): Track the largest values and associated data in a set of values
- [rollup()](/docs/reference/toolkit/minimum-and-maximum/max_n_by/rollup/index.md): Combine multiple MaxNBy aggregates
- [into_array()](/docs/reference/toolkit/minimum-and-maximum/max_n/into_array/index.md): Returns an array of the highest values from a MaxN aggregate
- [into_values()](/docs/reference/toolkit/minimum-and-maximum/max_n/into_values/index.md): Returns the highest values from a MaxN aggregate
- [max_n()](/docs/reference/toolkit/minimum-and-maximum/max_n/max_n/index.md): Find the largest values in a set of data
- [rollup()](/docs/reference/toolkit/minimum-and-maximum/max_n/rollup/index.md): Combine multiple MaxN aggregates
- [Minimum values overview](/docs/reference/toolkit/minimum-and-maximum/min_n/index.md): Get the N smallest values from a column
- [Minimum values by overview](/docs/reference/toolkit/minimum-and-maximum/min_n_by/index.md): Get the N smallest values with accompanying data
- [into_values()](/docs/reference/toolkit/minimum-and-maximum/min_n_by/into_values/index.md): Returns the lowest values and associated data from a MinNBy aggregate
- [min_n_by()](/docs/reference/toolkit/minimum-and-maximum/min_n_by/min_n_by/index.md): Track the smallest values and associated data in a set of values
- [rollup()](/docs/reference/toolkit/minimum-and-maximum/min_n_by/rollup/index.md): Combine multiple MinNBy aggregates
- [into_array()](/docs/reference/toolkit/minimum-and-maximum/min_n/into_array/index.md): Returns an array of the lowest values from a MinN aggregate
- [into_values()](/docs/reference/toolkit/minimum-and-maximum/min_n/into_values/index.md): Returns the lowest values from a MinN aggregate
- [min_n()](/docs/reference/toolkit/minimum-and-maximum/min_n/min_n/index.md): Find the smallest values in a set of data
- [rollup()](/docs/reference/toolkit/minimum-and-maximum/min_n/rollup/index.md): Combine multiple MinN aggregates
- [Percentile approximation overview](/docs/reference/toolkit/percentile-approximation/index.md): Estimate percentile values and percentile ranks using memory-efficient approximation algorithms
- [t-digest overview](/docs/reference/toolkit/percentile-approximation/tdigest/index.md): Percentile approximation optimized for extreme quantiles using the t-digest algorithm
- [approx_percentile()](/docs/reference/toolkit/percentile-approximation/tdigest/approx_percentile/index.md): Estimate the value at a given percentile from a `tdigest`
- [approx_percentile_rank()](/docs/reference/toolkit/percentile-approximation/tdigest/approx_percentile_rank/index.md): Estimate the percentile of a given value from a `tdigest`
- [max_val()](/docs/reference/toolkit/percentile-approximation/tdigest/max_val/index.md): Get the maximum value from a `tdigest`
- [mean()](/docs/reference/toolkit/percentile-approximation/tdigest/mean/index.md): Calculate the exact mean from values in a `tdigest`
- [min_val()](/docs/reference/toolkit/percentile-approximation/tdigest/min_val/index.md): Get the minimum value from a `tdigest`
- [num_vals()](/docs/reference/toolkit/percentile-approximation/tdigest/num_vals/index.md): Get the number of values contained in a `tdigest`
- [rollup()](/docs/reference/toolkit/percentile-approximation/tdigest/rollup/index.md): Roll up multiple `tdigest`s
- [tdigest()](/docs/reference/toolkit/percentile-approximation/tdigest/tdigest/index.md): Aggregate data in a `tdigest` for further calculation of percentile estimates
- [total()](/docs/reference/toolkit/percentile-approximation/tdigest/total/index.md): Calculate the exact sum of the values in a `tdigest`
- [UddSketch overview](/docs/reference/toolkit/percentile-approximation/uddsketch/index.md): Percentile approximation with guaranteed relative error using the UddSketch algorithm
- [approx_percentile()](/docs/reference/toolkit/percentile-approximation/uddsketch/approx_percentile/index.md): Estimate the value at a given percentile from a `uddsketch`
- [approx_percentile_array()](/docs/reference/toolkit/percentile-approximation/uddsketch/approx_percentile_array/index.md): Estimate the values for an array of given percentiles from a `uddsketch`
- [approx_percentile_rank()](/docs/reference/toolkit/percentile-approximation/uddsketch/approx_percentile_rank/index.md): Estimate the percentile of a given value from a `uddsketch`
- [error()](/docs/reference/toolkit/percentile-approximation/uddsketch/error/index.md): Get the maximum relative error for a `uddsketch`
- [mean()](/docs/reference/toolkit/percentile-approximation/uddsketch/mean/index.md): Calculate the exact mean from values in a `uddsketch`
- [num_vals()](/docs/reference/toolkit/percentile-approximation/uddsketch/num_vals/index.md): Get the number of values contained in a `uddsketch`
- [percentile_agg()](/docs/reference/toolkit/percentile-approximation/uddsketch/percentile_agg/index.md): Aggregate data in a uddsketch, using some reasonable default values, for further calculation of percentile estimates
- [rollup()](/docs/reference/toolkit/percentile-approximation/uddsketch/rollup/index.md): Roll up multiple `uddsketch`es
- [total()](/docs/reference/toolkit/percentile-approximation/uddsketch/total/index.md): Calculate the exact sum of the values in a `uddsketch`
- [uddsketch()](/docs/reference/toolkit/percentile-approximation/uddsketch/uddsketch/index.md): Aggregate data in a `uddsketch` for further calculation of percentile estimates
- [Saturating math overview](/docs/reference/toolkit/saturating-math/index.md): Perform saturating math operations on integers
- [saturating_add()](/docs/reference/toolkit/saturating-math/saturating_add/index.md): Add two numbers, saturating at the 32-bit integer bounds instead of overflowing
- [saturating_add_pos()](/docs/reference/toolkit/saturating-math/saturating_add_pos/index.md): Add two numbers, saturating at 0 for the minimum bound
- [saturating_mul()](/docs/reference/toolkit/saturating-math/saturating_mul/index.md): Multiply two numbers, saturating at the 32-bit integer bounds instead of overflowing
- [saturating_sub()](/docs/reference/toolkit/saturating-math/saturating_sub/index.md): Subtract one number from another, saturating at the 32-bit integer bounds instead of overflowing
- [saturating_sub_pos()](/docs/reference/toolkit/saturating-math/saturating_sub_pos/index.md): Subtract one number from another, saturating at 0 for the minimum bound
- [State tracking overview](/docs/reference/toolkit/state-tracking/index.md): Functions for tracking state transitions and system liveness over time
- [Compact state aggregation overview](/docs/reference/toolkit/state-tracking/compact_state_agg/index.md): Track the amount of time spent in each discrete state with compact_state_agg functions
- [compact_state_agg()](/docs/reference/toolkit/state-tracking/compact_state_agg/compact_state_agg/index.md): Aggregate state data into a state aggregate for further analysis
- [duration_in()](/docs/reference/toolkit/state-tracking/compact_state_agg/duration_in/index.md): Calculate the total time spent in a given state from a state aggregate
- [interpolated_duration_in()](/docs/reference/toolkit/state-tracking/compact_state_agg/interpolated_duration_in/index.md): Calculate the total time spent in a given state from a state aggregate, interpolating values at time bucket boundaries
- [into_values()](/docs/reference/toolkit/state-tracking/compact_state_agg/into_values/index.md): Expand a state aggregate into a set of rows displaying the duration of each state
- [rollup()](/docs/reference/toolkit/state-tracking/compact_state_agg/rollup/index.md): Combine multiple state aggregates
- [Heartbeat aggregation overview](/docs/reference/toolkit/state-tracking/heartbeat_agg/index.md): Determine system liveness from timestamped heartbeats with heartbeat_agg functions
- [dead_ranges()](/docs/reference/toolkit/state-tracking/heartbeat_agg/dead_ranges/index.md): Get the down intervals from a heartbeat_agg
- [downtime()](/docs/reference/toolkit/state-tracking/heartbeat_agg/downtime/index.md): Get the total time dead during a heartbeat aggregate
- [heartbeat_agg()](/docs/reference/toolkit/state-tracking/heartbeat_agg/heartbeat_agg/index.md): Create a liveness aggregate from a set of heartbeats
- [interpolate()](/docs/reference/toolkit/state-tracking/heartbeat_agg/interpolate/index.md): Adjust a heartbeat aggregate with predecessor information
- [interpolated_downtime()](/docs/reference/toolkit/state-tracking/heartbeat_agg/interpolated_downtime/index.md): Get the total time dead from a heartbeat aggregate and predecessor
- [interpolated_uptime()](/docs/reference/toolkit/state-tracking/heartbeat_agg/interpolated_uptime/index.md): Get the total time live from a heartbeat aggregate and predecessor
- [live_at()](/docs/reference/toolkit/state-tracking/heartbeat_agg/live_at/index.md): Test if the aggregate has a heartbeat covering a given time
- [live_ranges()](/docs/reference/toolkit/state-tracking/heartbeat_agg/live_ranges/index.md): Get the live intervals from a heartbeat_agg
- [num_gaps()](/docs/reference/toolkit/state-tracking/heartbeat_agg/num_gaps/index.md): Count the number of gaps between live ranges
- [num_live_ranges()](/docs/reference/toolkit/state-tracking/heartbeat_agg/num_live_ranges/index.md): Count the number of live ranges
- [rollup()](/docs/reference/toolkit/state-tracking/heartbeat_agg/rollup/index.md): Combine multiple heartbeat aggregates
- [trim_to()](/docs/reference/toolkit/state-tracking/heartbeat_agg/trim_to/index.md): Reduce the covered interval of a heartbeat aggregate
- [uptime()](/docs/reference/toolkit/state-tracking/heartbeat_agg/uptime/index.md): Get the total time live during a heartbeat aggregate
- [State aggregation overview](/docs/reference/toolkit/state-tracking/state_agg/index.md): Track transitions between discrete states with state_agg functions
- [duration_in()](/docs/reference/toolkit/state-tracking/state_agg/duration_in/index.md): Calculate the total time spent in a given state from a state aggregate
- [interpolated_duration_in()](/docs/reference/toolkit/state-tracking/state_agg/interpolated_duration_in/index.md): Calculate the total time spent in a given state from a state aggregate, interpolating values at time bucket boundaries
- [interpolated_state_periods()](/docs/reference/toolkit/state-tracking/state_agg/interpolated_state_periods/index.md): Get the time periods corresponding to a given state from a state aggregate, interpolating values at time bucket boundaries
- [interpolated_state_timeline()](/docs/reference/toolkit/state-tracking/state_agg/interpolated_state_timeline/index.md): Get a timeline of all states from a state aggregate, interpolating values at time bucket boundaries
- [into_values()](/docs/reference/toolkit/state-tracking/state_agg/into_values/index.md): Expand the state aggregate into a set of rows, displaying the duration of each state
- [rollup()](/docs/reference/toolkit/state-tracking/state_agg/rollup/index.md): Combine multiple state aggregates
- [state_agg()](/docs/reference/toolkit/state-tracking/state_agg/state_agg/index.md): Aggregate state data into a state aggregate for further analysis
- [state_at()](/docs/reference/toolkit/state-tracking/state_agg/state_at/index.md): Determine the state at a given time
- [state_periods()](/docs/reference/toolkit/state-tracking/state_agg/state_periods/index.md): Get the time periods corresponding to a given state from a state aggregate
- [state_timeline()](/docs/reference/toolkit/state-tracking/state_agg/state_timeline/index.md): Get a timeline of all states from a state aggregate
- [Statistical and regression analysis overview](/docs/reference/toolkit/statistical-and-regression-analysis/index.md): Functions for statistical analysis and linear regression on time-series data
- [stats_agg (one variable) overview](/docs/reference/toolkit/statistical-and-regression-analysis/stats_agg-one-variable/index.md): Statistical analysis functions for one-dimensional data
- [average()](/docs/reference/toolkit/statistical-and-regression-analysis/stats_agg-one-variable/average/index.md): Calculate the average from a one-dimensional statistical aggregate
- [kurtosis()](/docs/reference/toolkit/statistical-and-regression-analysis/stats_agg-one-variable/kurtosis/index.md): Calculate the kurtosis from a one-dimensional statistical aggregate
- [num_vals()](/docs/reference/toolkit/statistical-and-regression-analysis/stats_agg-one-variable/num_vals/index.md): Calculate the number of values in a one-dimensional statistical aggregate
- [rolling()](/docs/reference/toolkit/statistical-and-regression-analysis/stats_agg-one-variable/rolling/index.md): Combine multiple one-dimensional statistical aggregates to calculate rolling window aggregates
- [rollup()](/docs/reference/toolkit/statistical-and-regression-analysis/stats_agg-one-variable/rollup/index.md): Combine multiple one-dimensional statistical aggregates
- [skewness()](/docs/reference/toolkit/statistical-and-regression-analysis/stats_agg-one-variable/skewness/index.md): Calculate the skewness from a one-dimensional statistical aggregate
- [stats_agg() (one variable)](/docs/reference/toolkit/statistical-and-regression-analysis/stats_agg-one-variable/stats_agg/index.md): Aggregate data into an intermediate statistical aggregate form for further calculation
- [stddev()](/docs/reference/toolkit/statistical-and-regression-analysis/stats_agg-one-variable/stddev/index.md): Calculate the standard deviation from a one-dimensional statistical aggregate
- [sum()](/docs/reference/toolkit/statistical-and-regression-analysis/stats_agg-one-variable/sum/index.md): Calculate the sum from a one-dimensional statistical aggregate
- [variance()](/docs/reference/toolkit/statistical-and-regression-analysis/stats_agg-one-variable/variance/index.md): Calculate the variance from a one-dimensional statistical aggregate
- [stats_agg (two variables) overview](/docs/reference/toolkit/statistical-and-regression-analysis/stats_agg-two-variables/index.md): Statistical analysis and linear regression functions for two-dimensional data
- [average_y() | average_x()](/docs/reference/toolkit/statistical-and-regression-analysis/stats_agg-two-variables/average_y_x/index.md): Calculate the average from a two-dimensional statistical aggregate for the dimension specified
- [corr()](/docs/reference/toolkit/statistical-and-regression-analysis/stats_agg-two-variables/corr/index.md): Calculate the correlation coefficient from a two-dimensional statistical aggregate
- [covariance()](/docs/reference/toolkit/statistical-and-regression-analysis/stats_agg-two-variables/covariance/index.md): Calculate the covariance from a two-dimensional statistical aggregate
- [determination_coeff()](/docs/reference/toolkit/statistical-and-regression-analysis/stats_agg-two-variables/determination_coeff/index.md): Calculate the determination coefficient from a two-dimensional statistical aggregate
- [intercept()](/docs/reference/toolkit/statistical-and-regression-analysis/stats_agg-two-variables/intercept/index.md): Calculate the intercept from a two-dimensional statistical aggregate
- [kurtosis_y() | kurtosis_x()](/docs/reference/toolkit/statistical-and-regression-analysis/stats_agg-two-variables/kurtosis_y_x/index.md): Calculate the kurtosis from a two-dimensional statistical aggregate for the dimension specified
- [num_vals()](/docs/reference/toolkit/statistical-and-regression-analysis/stats_agg-two-variables/num_vals/index.md): Calculate the number of values in a two-dimensional statistical aggregate
- [rolling()](/docs/reference/toolkit/statistical-and-regression-analysis/stats_agg-two-variables/rolling/index.md): Combine multiple two-dimensional statistical aggregates to calculate rolling window aggregates
- [rollup()](/docs/reference/toolkit/statistical-and-regression-analysis/stats_agg-two-variables/rollup/index.md): Combine multiple two-dimensional statistical aggregates
- [skewness_y() | skewness_x()](/docs/reference/toolkit/statistical-and-regression-analysis/stats_agg-two-variables/skewness_y_x/index.md): Calculate the skewness from a two-dimensional statistical aggregate for the dimension specified
- [slope()](/docs/reference/toolkit/statistical-and-regression-analysis/stats_agg-two-variables/slope/index.md): Calculate the slope from a two-dimensional statistical aggregate
- [stats_agg() (two variables)](/docs/reference/toolkit/statistical-and-regression-analysis/stats_agg-two-variables/stats_agg/index.md): Aggregate data into an intermediate statistical aggregate form for further calculation
- [stddev_y() | stddev_x()](/docs/reference/toolkit/statistical-and-regression-analysis/stats_agg-two-variables/stddev_y_x/index.md): Calculate the standard deviation from a two-dimensional statistical aggregate for the dimension specified
- [sum_y() | sum_x()](/docs/reference/toolkit/statistical-and-regression-analysis/stats_agg-two-variables/sum_y_x/index.md): Calculate the sum from a two-dimensional statistical aggregate for the dimension specified
- [variance_y() | variance_x()](/docs/reference/toolkit/statistical-and-regression-analysis/stats_agg-two-variables/variance_y_x/index.md): Calculate the variance from a two-dimensional statistical aggregate for the dimension specified
- [x_intercept()](/docs/reference/toolkit/statistical-and-regression-analysis/stats_agg-two-variables/x_intercept/index.md): Calculate the x-intercept from a two-dimensional statistical aggregate
- [Time-weighted calculations overview](/docs/reference/toolkit/time_weight/index.md): Calculate time-weighted summary statistics for unevenly sampled data
- [average()](/docs/reference/toolkit/time_weight/average/index.md): Calculate the time-weighted average of values in a TimeWeightSummary
- [first_time()](/docs/reference/toolkit/time_weight/first_time/index.md): Get the first timestamp from a TimeWeightSummary aggregate
- [first_val()](/docs/reference/toolkit/time_weight/first_val/index.md): Get the first value from a TimeWeightSummary aggregate
- [integral()](/docs/reference/toolkit/time_weight/integral/index.md): Calculate the integral from a TimeWeightSummary
- [interpolated_average()](/docs/reference/toolkit/time_weight/interpolated_average/index.md): Calculate the time-weighted average over an interval, while interpolating the interval bounds
- [interpolated_integral()](/docs/reference/toolkit/time_weight/interpolated_integral/index.md): Calculate the integral over an interval, while interpolating the interval bounds
- [last_time()](/docs/reference/toolkit/time_weight/last_time/index.md): Get the last timestamp from a TimeWeightSummary aggregate
- [last_val()](/docs/reference/toolkit/time_weight/last_val/index.md): Get the last value from a TimeWeightSummary aggregate
- [rollup()](/docs/reference/toolkit/time_weight/rollup/index.md): Combine multiple TimeWeightSummaries
- [time_weight()](/docs/reference/toolkit/time_weight/time_weight/index.md): Aggregate data into an intermediate time-weighted aggregate form for further calculation
- [Timevector overview](/docs/reference/toolkit/timevector/index.md): Efficiently represent and process time-series data with timevector objects and pipeline operations
- [rollup()](/docs/reference/toolkit/timevector/rollup/index.md): Combine multiple timevectors into a single timevector for re-aggregation
- [timevector()](/docs/reference/toolkit/timevector/timevector/index.md): Create a timevector from time-value pairs for efficient time-series processing
- [unnest()](/docs/reference/toolkit/timevector/unnest/index.md): Extract time-value pairs from a timevector back into rows
- [Learn](/docs/tutorials/index.md): Walk through a variety of scenarios that use example datasets, and enable yourself to get the best out of Tiger Data products.

## API Reference

Links below point to language-neutral HTTP documentation. SDK-specific docs follow the same URL structure with the language inserted after the base path: `/reference/tiger-cloud-rest/{language}/resources/...`.

Available languages: http

### [Auth](/docs/reference/tiger-cloud-rest/resources/auth/index.md)

- [Retrieve Info](/docs/reference/tiger-cloud-rest/resources/auth/methods/retrieve_info/index.md): Get Authentication Info


### [Projects](/docs/reference/tiger-cloud-rest/resources/projects/index.md)

- [Get](/docs/reference/tiger-cloud-rest/resources/projects/methods/get/index.md): List projects accessible to the authenticated caller

- [Vpcs](/docs/reference/tiger-cloud-rest/resources/projects/subresources/vpcs/index.md)

  - [List](/docs/reference/tiger-cloud-rest/resources/projects/subresources/vpcs/methods/list/index.md): List All VPCs
  - [Create](/docs/reference/tiger-cloud-rest/resources/projects/subresources/vpcs/methods/create/index.md): Create a VPC
  - [Retrieve](/docs/reference/tiger-cloud-rest/resources/projects/subresources/vpcs/methods/retrieve/index.md): Get a VPC
  - [Delete](/docs/reference/tiger-cloud-rest/resources/projects/subresources/vpcs/methods/delete/index.md): Delete a VPC
  - [Rename](/docs/reference/tiger-cloud-rest/resources/projects/subresources/vpcs/methods/rename/index.md): Rename a VPC

  - [Peerings](/docs/reference/tiger-cloud-rest/resources/projects/subresources/vpcs/subresources/peerings/index.md)

    - [List](/docs/reference/tiger-cloud-rest/resources/projects/subresources/vpcs/subresources/peerings/methods/list/index.md): List VPC Peerings
    - [Create](/docs/reference/tiger-cloud-rest/resources/projects/subresources/vpcs/subresources/peerings/methods/create/index.md): Create a VPC Peering
    - [Retrieve](/docs/reference/tiger-cloud-rest/resources/projects/subresources/vpcs/subresources/peerings/methods/retrieve/index.md): Get a VPC Peering
    - [Delete](/docs/reference/tiger-cloud-rest/resources/projects/subresources/vpcs/subresources/peerings/methods/delete/index.md): Delete a VPC Peering

- [Services](/docs/reference/tiger-cloud-rest/resources/projects/subresources/services/index.md)

  - [List](/docs/reference/tiger-cloud-rest/resources/projects/subresources/services/methods/list/index.md): List All Services
  - [Create](/docs/reference/tiger-cloud-rest/resources/projects/subresources/services/methods/create/index.md): Create a Service
  - [Retrieve](/docs/reference/tiger-cloud-rest/resources/projects/subresources/services/methods/retrieve/index.md): Get a Service
  - [Delete](/docs/reference/tiger-cloud-rest/resources/projects/subresources/services/methods/delete/index.md): Delete a Service
  - [Start](/docs/reference/tiger-cloud-rest/resources/projects/subresources/services/methods/start/index.md): Start a Service
  - [Stop](/docs/reference/tiger-cloud-rest/resources/projects/subresources/services/methods/stop/index.md): Stop a Service
  - [Attach To Vpc](/docs/reference/tiger-cloud-rest/resources/projects/subresources/services/methods/attach_to_vpc/index.md): Attach Service to VPC
  - [Detach From Vpc](/docs/reference/tiger-cloud-rest/resources/projects/subresources/services/methods/detach_from_vpc/index.md): Detach Service from VPC
  - [Resize](/docs/reference/tiger-cloud-rest/resources/projects/subresources/services/methods/resize/index.md): Resize a Service
  - [Enable Pooler](/docs/reference/tiger-cloud-rest/resources/projects/subresources/services/methods/enable_pooler/index.md): Enable Connection Pooler for a Service
  - [Disable Pooler](/docs/reference/tiger-cloud-rest/resources/projects/subresources/services/methods/disable_pooler/index.md): Disable Connection Pooler for a Service
  - [Fork Service](/docs/reference/tiger-cloud-rest/resources/projects/subresources/services/methods/fork_service/index.md): Fork a Service
  - [Update Password](/docs/reference/tiger-cloud-rest/resources/projects/subresources/services/methods/update_password/index.md): Update Service Password
  - [Set Environment](/docs/reference/tiger-cloud-rest/resources/projects/subresources/services/methods/set_environment/index.md): Set Environment for a Service
  - [Logs](/docs/reference/tiger-cloud-rest/resources/projects/subresources/services/methods/logs/index.md): Get service logs
  - [Set Ha](/docs/reference/tiger-cloud-rest/resources/projects/subresources/services/methods/set_ha/index.md): Change HA configuration for a Service

  - [Replica Sets](/docs/reference/tiger-cloud-rest/resources/projects/subresources/services/subresources/replica_sets/index.md)

    - [Retrieve Replica Sets](/docs/reference/tiger-cloud-rest/resources/projects/subresources/services/subresources/replica_sets/methods/retrieve_replica_sets/index.md): Get Read Replica Sets
    - [Replica Sets](/docs/reference/tiger-cloud-rest/resources/projects/subresources/services/subresources/replica_sets/methods/replica_sets/index.md): Create a Read Replica Set
    - [Delete](/docs/reference/tiger-cloud-rest/resources/projects/subresources/services/subresources/replica_sets/methods/delete/index.md): Delete a Read Replica Set
    - [Resize](/docs/reference/tiger-cloud-rest/resources/projects/subresources/services/subresources/replica_sets/methods/resize/index.md): Resize a Read Replica Set
    - [Enable Pooler](/docs/reference/tiger-cloud-rest/resources/projects/subresources/services/subresources/replica_sets/methods/enable_pooler/index.md): Enable Connection Pooler for a Read Replica
    - [Disable Pooler](/docs/reference/tiger-cloud-rest/resources/projects/subresources/services/subresources/replica_sets/methods/disable_pooler/index.md): Disable Connection Pooler for a Read Replica
    - [Set Environment](/docs/reference/tiger-cloud-rest/resources/projects/subresources/services/subresources/replica_sets/methods/set_environment/index.md): Set Environment for a Read Replica