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Tiger MCP vs. a Generic Postgres MCP Server
Time Series Forecasting with PostgreSQL: Methods, SQL Examples, and When to Use PythonTime-Series Analysis and Forecasting With Python Why Consider Using PostgreSQL for Time-Series Data?Time-Series Analysis in RWhat Is Temporal Data?Understanding Autoregressive Time-Series ModelingAlternatives to TimescaleStationary Time-Series AnalysisWhat Are Open-Source Time-Series Databases—Understanding Your OptionsIs Your Data Time Series? Data Types Supported by PostgreSQL and TimescaleUnderstanding Database Workloads: Variable, Bursty, and Uniform PatternsThe Best Time-Series Databases Compared (2026)Time Series Anomaly Detection: Methods, SQL, and Real-Time ImplementationAWS Timestream Alternatives: Your Migration Options After LiveAnalyticsTime-Series Database: What It Is, How It Works, and When You Need OneWhat Is a Time Series and How Is It Used?How to Work With Time Series in Python?Tools for Working With Time-Series Analysis in PythonGuide to Time-Series Analysis in PythonCreating a Fast Time-Series Graph With Postgres Materialized Views
OpenTelemetry Backend: Choosing Metrics Storage That Doesn't Lock You InGPU Cluster Monitoring: The Database Behind AI Infrastructure TelemetryWhat Is DCIM Software, and What Database Does It Use?Data Center Power Monitoring: The Database Layer Behind PUE, PDU, and Sustainability MetricsPrometheus Long-Term Storage: Thanos, Mimir, VictoriaMetrics, and PostgreSQL Compared
Understanding PostgreSQLUnderstanding SQL Aggregate FunctionsUnderstanding the rank() and dense_rank() Functions in PostgreSQLUnderstanding percentile_cont() and percentile_disc() in PostgreSQLStructured vs. Semi-Structured vs. Unstructured Data in PostgreSQLOptimizing Your Database: A Deep Dive into PostgreSQL Data TypesPostgres Cheat SheetHow to Address ‘Error: Could Not Resize Shared Memory Segment’ Understanding the Postgres extract() FunctionUnderstanding FROM in PostgreSQL (With Examples)How to Install PostgreSQL on LinuxHow to Install PostgreSQL on MacOSUnderstanding FILTER in PostgreSQL (With Examples)Understanding HAVING in PostgreSQL (With Examples)5 Common Connection Errors in PostgreSQL and How to Solve ThemUnderstanding GROUP BY in PostgreSQL (With Examples)How to Fix No Partition of Relation Found for Row in Postgres DatabasesUnderstanding LIMIT in PostgreSQL (With Examples)How to Fix Transaction ID Wraparound ExhaustionUnderstanding ORDER BY in PostgreSQL (With Examples)Understanding PostgreSQL FunctionsUnderstanding WINDOW in PostgreSQL (With Examples)Understanding PostgreSQL WITHIN GROUPPostgreSQL Mathematical Functions: Enhancing Coding EfficiencyUnderstanding DISTINCT in PostgreSQL (With Examples)Understanding WHERE in PostgreSQL (With Examples)Understanding OFFSET in PostgreSQL (With Examples)Understanding the Postgres string_agg FunctionUnderstanding PostgreSQL SELECTWhat Characters Are Allowed in PostgreSQL Strings?What Is Data Transformation, and Why Is It Important?What Is Data Compression and How Does It Work?Using PostgreSQL UPDATE With JOINUnderstanding PostgreSQL User-Defined FunctionsUnderstanding Foreign Keys in PostgreSQLData Processing With PostgreSQL Window FunctionsUnderstanding PostgreSQL Date and Time FunctionsWhat Is a PostgreSQL Full Outer Join?What Is a PostgreSQL Inner Join?What Is a PostgreSQL Left Join? And a Right Join?PostgreSQL Join Type TheoryA Guide to PostgreSQL ViewsStrategies for Improving Postgres JOIN PerformanceUnderstanding PostgreSQL's COALESCE FunctionUnderstanding PostgreSQL Array FunctionsUnderstanding PostgreSQL Conditional FunctionsUsing PostgreSQL String Functions for Improved Data AnalysisPostgreSQL vs. Cassandra: The Decision Framework for Time-Series and Write-Heavy WorkloadsPostgreSQL Joins : A SummaryWhat Is a PostgreSQL Cross Join?Data Partitioning: What It Is and Why It MattersSelf-Hosted or Cloud Database? A Countryside Reflection on Infrastructure ChoicesUnderstanding ACID Compliance
Connect Your AI Coding Agent to Tiger Cloud: Setup for Cursor, Claude Code, VS Code, and MoreHow to Monitor and Optimize PostgreSQL Index PerformanceGuide to PostgreSQL PerformancePostgreSQL Performance Tuning: Designing and Implementing Your Database SchemaPostgreSQL Performance Tuning: Key ParametersPostgreSQL Performance Tuning: Optimizing Database IndexesDetermining the Optimal Postgres Partition SizeWhen to Consider Postgres PartitioningAn Intro to Data Modeling on PostgreSQLDesigning Your Database Schema: Wide vs. Narrow Postgres TablesGuide to PostgreSQL Database OperationsBest Practices for Time-Series Data Modeling: Single or Multiple Partitioned Table(s) a.k.a. Hypertables Best Practices for (Time-)Series Metadata Tables A PostgreSQL Database Replication GuideA Guide to Data Analysis on PostgreSQLHow to Query JSONB in PostgreSQLHow to Compute Standard Deviation With PostgreSQLPostgreSQL Performance Tuning: How to Size Your DatabaseSQL/JSON Data Model and JSON in SQL: A PostgreSQL PerspectiveUnderstanding PostgreSQL TablespacesTop PostgreSQL Drivers for PythonPg_partman vs. Hypertables for Postgres PartitioningExplaining PostgreSQL EXPLAINGuide to PostgreSQL Database DesignHow PostgreSQL Data Aggregation WorksBuilding a Scalable DatabaseA Guide to pg_restore (and pg_restore Example)How to Index JSONB Columns in PostgreSQLWhat Is Audit Logging and How to Enable It in PostgreSQLOptimizing Array Queries With GIN Indexes in PostgreSQLHow to Reduce Bloat in Large PostgreSQL TablesGuide to PostgreSQL SecurityHow to Query JSON Metadata in PostgreSQLRecursive Query in SQL: What It Is, and How to Write OneNavigating Growing PostgreSQL Tables With Partitioning (and More)What Is a PostgreSQL Temporary View?How to Use PostgreSQL for Data TransformationHandling Large Objects in PostgresHow to Use Psycopg2: The PostgreSQL Adapter for PythonA Guide to Scaling PostgreSQLAWS Timestream for InfluxDB Alternative: When You Need to Look FurtherHow to Migrate from AWS Timestream to PostgreSQL: A Technical GuideHow to Choose a Database: A Decision Framework for Modern ApplicationsGuide to Postgres Data Management
Time-Series Database High Availability and Disaster RecoveryBest Practices for Scaling PostgreSQLHow to Store Video in PostgreSQL Using BYTEABest Practices for Postgres PerformanceHow to Design Your PostgreSQL Database: Two Schema ExamplesBest Practices for PostgreSQL Database OperationsHow to Manage Your Data With Data Retention PoliciesBest Practices for PostgreSQL Data AnalysisBest Practices for PostgreSQL AggregationBest Practices for Postgres Database ReplicationBest Practices for Postgres Data ManagementHow to Use a Common Table Expression (CTE) in SQLHow to Use PostgreSQL for Data NormalizationTesting Postgres Ingest: INSERT vs. Batch INSERT vs. COPYBest Practices for Postgres SecurityHow to Handle High-Cardinality Data in PostgreSQLPostgreSQL Compression: Every Option, When To Use Each, and What To Expect
The Best PostgreSQL Extensions for Analytics Workloads: A Field GuidePostgreSQL Extensions: amcheckPostgreSQL Extensions: Unlocking Multidimensional Points With Cube PostgreSQL Extensions: hstorePostgreSQL Extensions: ltreePostgreSQL Extensions: Secure Your Time-Series Data With pgcryptoPostgreSQL Extensions: pg_prewarmPostgreSQL Extensions: pgRoutingPostgreSQL Extensions: pg_stat_statementsPostgreSQL Extensions: Database Testing With pgTAPPostgreSQL Extensions: Install pg_trgm for Data MatchingPostgreSQL Extensions: PL/pgSQLPostgreSQL Extensions: Using PostGIS and Timescale for Advanced Geospatial InsightsPostgreSQL Extensions: Intro to uuid-osspTurning PostgreSQL Into a Vector Database With pgvector
What Is ClickHouse and How Does It Compare to PostgreSQL and TimescaleDB for Time Series?Timescale vs. Amazon RDS PostgreSQL: Up to 350x Faster Queries, 44 % Faster Ingest, 95 % Storage Savings for Time-Series DataWhat We Learned From Benchmarking Amazon Aurora PostgreSQL ServerlessTimescaleDB vs. Amazon Timestream: 6,000x Higher Inserts, 5-175x Faster Queries, 150-220x CheaperHow to Store Time-Series Data in MongoDB and Why That’s a Bad IdeaPostgreSQL + TimescaleDB: 1,000x Faster Queries, 90 % Data Compression, and Much MoreEye or the Tiger: Benchmarking Cassandra vs. TimescaleDB for Time-Series Data
MES Data Architecture: Modeling Work Orders, Genealogy, and Historian IntegrationMeter Data Management: Why AMI Interval Data Breaks Legacy MDM SystemsGeofencing and Driver Behavior Analytics: How to Store Both in One DatabaseWhich Database for a Digital Twin? Digital Twin Database Options ComparedGrid Modernization: Why the Data Layer Decides Whether It WorksFleet Telemetry Database: How to Store and Query Vehicle Sensor Data at ScaleUnderstanding IoT (Internet of Things)A Beginner’s Guide to IIoT and Industry 4.0DERMS Database: Solving the Single Source of DER Data ProblemForecasting the Physical World: Foundation Models for Predictive MaintenanceBuilding Energy Management System: The Data Layer Behind Energy Monitoring, Sub-Metering, and M&VSmart Building Analytics: Turning BMS Telemetry Into Occupancy, Energy, and HVAC InsightEV Charging Load ManagementBuilding Management System Database: Architecture for BACnet, Modbus, and Smart Building Sensor Data at ScaleSmart Grid Data Platform: Architecting for SCADA, AMI, PMU, and DERMS Data at ScaleDigital Twin Architecture: The Database and Data Model Behind a Digital TwinCAN Bus Data Logger: Decoding DBC and J1939 Signals into PostgresPredictive Maintenance Database Architecture: Storing and Querying Sensor Data for Failure PredictionPhysical AI Telemetry: Database Architecture for Autonomous-Vehicle FleetsPlant Historian: What It Captures and Where the Analytics Layer BeginsManufacturing Analytics Database: Architecture for Real-Time Production DataRobot Fleet Telemetry: Database Architecture for AMR, Industrial Robot, and Service Robot DataData Center Monitoring: What Database Stores Your Telemetry?EV Charging Management System: Architecture, OCPP Data, and the Right DatabaseIIoT Database Requirements: Six Things Your Database Must DoWater Utilities Database: How to Store and Query SCADA, AMI, and Quality Data at ScaleWhat Is an Edge Database? On-Device Storage, Sync Patterns, and Choosing the Right StackData Historian vs. Time-Series Database: How to Choose and When to SwitchWhat Is a Data Historian?The Best Databases for IoT in 2026: A Practical ComparisonHow Hopthru Powers Real-Time Transit Analytics From a 1 TB TableStoring IoT Data: 8 Reasons Why You Should Use PostgreSQLHow to Simulate a Basic IoT Sensor Dataset on PostgreSQLFrom Ingest to Insights in Milliseconds: Everactive's Tech Transformation With TimescaleHow Ndustrial Is Providing Fast Real-Time Queries and Safely Storing Client Data With 97 % CompressionWhy You Should Use PostgreSQL for Industrial IoT Data Migrating a Low-Code IoT Platform Storing 20M Records/DayHow United Manufacturing Hub Is Introducing Open Source to ManufacturingBuilding IoT Pipelines for Faster Analytics With IoT CoreVisualizing IoT Data at Scale With Hopara and TimescaleDB
A Brief History of AI: How Did We Get Here, and What's Next?A Beginner’s Guide to Vector EmbeddingsPostgreSQL as a Vector Database: A Pgvector TutorialUsing Pgvector With PythonHow to Choose a Vector DatabaseVector Databases Are the Wrong AbstractionUnderstanding DiskANNA Guide to Cosine SimilarityStreaming DiskANN: How We Made PostgreSQL as Fast as Pinecone for Vector DataImplementing Cosine Similarity in PythonVector Database Basics: HNSWVector Database Options for AWSVector Store vs. Vector Database: Understanding the ConnectionPgvector vs. Pinecone: Vector Database Performance and Cost ComparisonHow to Build LLM Applications With Pgvector Vector Store in LangChainHow to Implement RAG With Amazon Bedrock and LangChainRAG Is More Than Just Vector SearchRefining Vector Search Queries With Time Filters in Pgvector: A TutorialUnderstanding Semantic SearchWhat Is Vector Search? Text-to-SQL: A Developer’s Zero-to-Hero GuideWhen Should You Use Full-Text Search vs. Vector Search?HNSW vs. DiskANNVector Search vs Semantic SearchBuilding AI Agents with Persistent Memory: A Unified Database ApproachNearest Neighbor Indexes: What Are IVFFlat Indexes in Pgvector and How Do They WorkPostgreSQL Hybrid Search Using Pgvector and CohereBuilding an AI Image Gallery With OpenAI CLIP, Claude Sonnet 3.5, and Pgvector
PostgreSQL OLTP: Transactions, Scale, and the Architecture That Makes It WorkHow to Choose an OLAP Database: A Practical Decision Guide (2026)Data Analytics vs. Real-Time Analytics: How to Pick Your Database (and Why It Should Be PostgreSQL)How to Choose a Real-Time Analytics DatabaseColumnar Databases vs. Row-Oriented Databases: Which to Choose?What Is the Best Database for Real-Time AnalyticsPostgreSQL as a Real-Time Analytics DatabaseUnderstanding OLAP: What It Is, How It Differs From OLTP, and Running It on PostgreSQLHow to Build an IoT Pipeline for Real-Time Analytics in PostgreSQL
Alternatives to RDSWhy Is RDS so Expensive? Understanding RDS Pricing and CostsEstimating RDS CostsHow to Migrate From AWS RDS for PostgreSQL to TimescaleAmazon Aurora vs. RDS: Understanding the Difference
5 InfluxDB Alternatives for Your Time-Series Data8 Reasons to Choose Timescale as Your InfluxDB Alternative InfluxQL, Flux, and SQL: Which Query Language Is Best? (With Cheatsheet)What InfluxDB Got WrongTimescaleDB vs. InfluxDB: Purpose Built Differently for Time-Series Data
5 Ways to Monitor Your PostgreSQL DatabaseHow to Migrate Your Data to Timescale (3 Ways)Postgres TOAST vs. Timescale CompressionBuilding Python Apps With PostgreSQL: A Developer's GuideData Visualization in PostgreSQL With Apache SupersetMore Time-Series Data Analysis, Fewer Lines of Code: Meet HyperfunctionsIs Postgres Partitioning Really That Hard? An Introduction To HypertablesPostgreSQL Materialized Views and Where to Find ThemTime-Series Downsampling: The Complete Guide to Tiered Data Resolution in SQLContinuous Aggregates: Incremental Materialized Views for Time-Series DataComplete Guide: Migrating from MongoDB to Tiger Data (Step-by-Step)Timescale Tips: Testing Your Chunk Size
Postgres cheat sheet
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Tiger MCP vs. a Generic Postgres MCP Server
Time Series Forecasting with PostgreSQL: Methods, SQL Examples, and When to Use PythonTime-Series Analysis and Forecasting With Python Why Consider Using PostgreSQL for Time-Series Data?Time-Series Analysis in RWhat Is Temporal Data?Understanding Autoregressive Time-Series ModelingAlternatives to TimescaleStationary Time-Series AnalysisWhat Are Open-Source Time-Series Databases—Understanding Your OptionsIs Your Data Time Series? Data Types Supported by PostgreSQL and TimescaleUnderstanding Database Workloads: Variable, Bursty, and Uniform PatternsThe Best Time-Series Databases Compared (2026)Time Series Anomaly Detection: Methods, SQL, and Real-Time ImplementationAWS Timestream Alternatives: Your Migration Options After LiveAnalyticsTime-Series Database: What It Is, How It Works, and When You Need OneWhat Is a Time Series and How Is It Used?How to Work With Time Series in Python?Tools for Working With Time-Series Analysis in PythonGuide to Time-Series Analysis in PythonCreating a Fast Time-Series Graph With Postgres Materialized Views
OpenTelemetry Backend: Choosing Metrics Storage That Doesn't Lock You InGPU Cluster Monitoring: The Database Behind AI Infrastructure TelemetryWhat Is DCIM Software, and What Database Does It Use?Data Center Power Monitoring: The Database Layer Behind PUE, PDU, and Sustainability MetricsPrometheus Long-Term Storage: Thanos, Mimir, VictoriaMetrics, and PostgreSQL Compared
Understanding PostgreSQLUnderstanding SQL Aggregate FunctionsUnderstanding the rank() and dense_rank() Functions in PostgreSQLUnderstanding percentile_cont() and percentile_disc() in PostgreSQLStructured vs. Semi-Structured vs. Unstructured Data in PostgreSQLOptimizing Your Database: A Deep Dive into PostgreSQL Data TypesPostgres Cheat SheetHow to Address ‘Error: Could Not Resize Shared Memory Segment’ Understanding the Postgres extract() FunctionUnderstanding FROM in PostgreSQL (With Examples)How to Install PostgreSQL on LinuxHow to Install PostgreSQL on MacOSUnderstanding FILTER in PostgreSQL (With Examples)Understanding HAVING in PostgreSQL (With Examples)5 Common Connection Errors in PostgreSQL and How to Solve ThemUnderstanding GROUP BY in PostgreSQL (With Examples)How to Fix No Partition of Relation Found for Row in Postgres DatabasesUnderstanding LIMIT in PostgreSQL (With Examples)How to Fix Transaction ID Wraparound ExhaustionUnderstanding ORDER BY in PostgreSQL (With Examples)Understanding PostgreSQL FunctionsUnderstanding WINDOW in PostgreSQL (With Examples)Understanding PostgreSQL WITHIN GROUPPostgreSQL Mathematical Functions: Enhancing Coding EfficiencyUnderstanding DISTINCT in PostgreSQL (With Examples)Understanding WHERE in PostgreSQL (With Examples)Understanding OFFSET in PostgreSQL (With Examples)Understanding the Postgres string_agg FunctionUnderstanding PostgreSQL SELECTWhat Characters Are Allowed in PostgreSQL Strings?What Is Data Transformation, and Why Is It Important?What Is Data Compression and How Does It Work?Using PostgreSQL UPDATE With JOINUnderstanding PostgreSQL User-Defined FunctionsUnderstanding Foreign Keys in PostgreSQLData Processing With PostgreSQL Window FunctionsUnderstanding PostgreSQL Date and Time FunctionsWhat Is a PostgreSQL Full Outer Join?What Is a PostgreSQL Inner Join?What Is a PostgreSQL Left Join? And a Right Join?PostgreSQL Join Type TheoryA Guide to PostgreSQL ViewsStrategies for Improving Postgres JOIN PerformanceUnderstanding PostgreSQL's COALESCE FunctionUnderstanding PostgreSQL Array FunctionsUnderstanding PostgreSQL Conditional FunctionsUsing PostgreSQL String Functions for Improved Data AnalysisPostgreSQL vs. Cassandra: The Decision Framework for Time-Series and Write-Heavy WorkloadsPostgreSQL Joins : A SummaryWhat Is a PostgreSQL Cross Join?Data Partitioning: What It Is and Why It MattersSelf-Hosted or Cloud Database? A Countryside Reflection on Infrastructure ChoicesUnderstanding ACID Compliance
Connect Your AI Coding Agent to Tiger Cloud: Setup for Cursor, Claude Code, VS Code, and MoreHow to Monitor and Optimize PostgreSQL Index PerformanceGuide to PostgreSQL PerformancePostgreSQL Performance Tuning: Designing and Implementing Your Database SchemaPostgreSQL Performance Tuning: Key ParametersPostgreSQL Performance Tuning: Optimizing Database IndexesDetermining the Optimal Postgres Partition SizeWhen to Consider Postgres PartitioningAn Intro to Data Modeling on PostgreSQLDesigning Your Database Schema: Wide vs. Narrow Postgres TablesGuide to PostgreSQL Database OperationsBest Practices for Time-Series Data Modeling: Single or Multiple Partitioned Table(s) a.k.a. Hypertables Best Practices for (Time-)Series Metadata Tables A PostgreSQL Database Replication GuideA Guide to Data Analysis on PostgreSQLHow to Query JSONB in PostgreSQLHow to Compute Standard Deviation With PostgreSQLPostgreSQL Performance Tuning: How to Size Your DatabaseSQL/JSON Data Model and JSON in SQL: A PostgreSQL PerspectiveUnderstanding PostgreSQL TablespacesTop PostgreSQL Drivers for PythonPg_partman vs. Hypertables for Postgres PartitioningExplaining PostgreSQL EXPLAINGuide to PostgreSQL Database DesignHow PostgreSQL Data Aggregation WorksBuilding a Scalable DatabaseA Guide to pg_restore (and pg_restore Example)How to Index JSONB Columns in PostgreSQLWhat Is Audit Logging and How to Enable It in PostgreSQLOptimizing Array Queries With GIN Indexes in PostgreSQLHow to Reduce Bloat in Large PostgreSQL TablesGuide to PostgreSQL SecurityHow to Query JSON Metadata in PostgreSQLRecursive Query in SQL: What It Is, and How to Write OneNavigating Growing PostgreSQL Tables With Partitioning (and More)What Is a PostgreSQL Temporary View?How to Use PostgreSQL for Data TransformationHandling Large Objects in PostgresHow to Use Psycopg2: The PostgreSQL Adapter for PythonA Guide to Scaling PostgreSQLAWS Timestream for InfluxDB Alternative: When You Need to Look FurtherHow to Migrate from AWS Timestream to PostgreSQL: A Technical GuideHow to Choose a Database: A Decision Framework for Modern ApplicationsGuide to Postgres Data Management
Time-Series Database High Availability and Disaster RecoveryBest Practices for Scaling PostgreSQLHow to Store Video in PostgreSQL Using BYTEABest Practices for Postgres PerformanceHow to Design Your PostgreSQL Database: Two Schema ExamplesBest Practices for PostgreSQL Database OperationsHow to Manage Your Data With Data Retention PoliciesBest Practices for PostgreSQL Data AnalysisBest Practices for PostgreSQL AggregationBest Practices for Postgres Database ReplicationBest Practices for Postgres Data ManagementHow to Use a Common Table Expression (CTE) in SQLHow to Use PostgreSQL for Data NormalizationTesting Postgres Ingest: INSERT vs. Batch INSERT vs. COPYBest Practices for Postgres SecurityHow to Handle High-Cardinality Data in PostgreSQLPostgreSQL Compression: Every Option, When To Use Each, and What To Expect
The Best PostgreSQL Extensions for Analytics Workloads: A Field GuidePostgreSQL Extensions: amcheckPostgreSQL Extensions: Unlocking Multidimensional Points With Cube PostgreSQL Extensions: hstorePostgreSQL Extensions: ltreePostgreSQL Extensions: Secure Your Time-Series Data With pgcryptoPostgreSQL Extensions: pg_prewarmPostgreSQL Extensions: pgRoutingPostgreSQL Extensions: pg_stat_statementsPostgreSQL Extensions: Database Testing With pgTAPPostgreSQL Extensions: Install pg_trgm for Data MatchingPostgreSQL Extensions: PL/pgSQLPostgreSQL Extensions: Using PostGIS and Timescale for Advanced Geospatial InsightsPostgreSQL Extensions: Intro to uuid-osspTurning PostgreSQL Into a Vector Database With pgvector
What Is ClickHouse and How Does It Compare to PostgreSQL and TimescaleDB for Time Series?Timescale vs. Amazon RDS PostgreSQL: Up to 350x Faster Queries, 44 % Faster Ingest, 95 % Storage Savings for Time-Series DataWhat We Learned From Benchmarking Amazon Aurora PostgreSQL ServerlessTimescaleDB vs. Amazon Timestream: 6,000x Higher Inserts, 5-175x Faster Queries, 150-220x CheaperHow to Store Time-Series Data in MongoDB and Why That’s a Bad IdeaPostgreSQL + TimescaleDB: 1,000x Faster Queries, 90 % Data Compression, and Much MoreEye or the Tiger: Benchmarking Cassandra vs. TimescaleDB for Time-Series Data
MES Data Architecture: Modeling Work Orders, Genealogy, and Historian IntegrationMeter Data Management: Why AMI Interval Data Breaks Legacy MDM SystemsGeofencing and Driver Behavior Analytics: How to Store Both in One DatabaseWhich Database for a Digital Twin? Digital Twin Database Options ComparedGrid Modernization: Why the Data Layer Decides Whether It WorksFleet Telemetry Database: How to Store and Query Vehicle Sensor Data at ScaleUnderstanding IoT (Internet of Things)A Beginner’s Guide to IIoT and Industry 4.0DERMS Database: Solving the Single Source of DER Data ProblemForecasting the Physical World: Foundation Models for Predictive MaintenanceBuilding Energy Management System: The Data Layer Behind Energy Monitoring, Sub-Metering, and M&VSmart Building Analytics: Turning BMS Telemetry Into Occupancy, Energy, and HVAC InsightEV Charging Load ManagementBuilding Management System Database: Architecture for BACnet, Modbus, and Smart Building Sensor Data at ScaleSmart Grid Data Platform: Architecting for SCADA, AMI, PMU, and DERMS Data at ScaleDigital Twin Architecture: The Database and Data Model Behind a Digital TwinCAN Bus Data Logger: Decoding DBC and J1939 Signals into PostgresPredictive Maintenance Database Architecture: Storing and Querying Sensor Data for Failure PredictionPhysical AI Telemetry: Database Architecture for Autonomous-Vehicle FleetsPlant Historian: What It Captures and Where the Analytics Layer BeginsManufacturing Analytics Database: Architecture for Real-Time Production DataRobot Fleet Telemetry: Database Architecture for AMR, Industrial Robot, and Service Robot DataData Center Monitoring: What Database Stores Your Telemetry?EV Charging Management System: Architecture, OCPP Data, and the Right DatabaseIIoT Database Requirements: Six Things Your Database Must DoWater Utilities Database: How to Store and Query SCADA, AMI, and Quality Data at ScaleWhat Is an Edge Database? On-Device Storage, Sync Patterns, and Choosing the Right StackData Historian vs. Time-Series Database: How to Choose and When to SwitchWhat Is a Data Historian?The Best Databases for IoT in 2026: A Practical ComparisonHow Hopthru Powers Real-Time Transit Analytics From a 1 TB TableStoring IoT Data: 8 Reasons Why You Should Use PostgreSQLHow to Simulate a Basic IoT Sensor Dataset on PostgreSQLFrom Ingest to Insights in Milliseconds: Everactive's Tech Transformation With TimescaleHow Ndustrial Is Providing Fast Real-Time Queries and Safely Storing Client Data With 97 % CompressionWhy You Should Use PostgreSQL for Industrial IoT Data Migrating a Low-Code IoT Platform Storing 20M Records/DayHow United Manufacturing Hub Is Introducing Open Source to ManufacturingBuilding IoT Pipelines for Faster Analytics With IoT CoreVisualizing IoT Data at Scale With Hopara and TimescaleDB
A Brief History of AI: How Did We Get Here, and What's Next?A Beginner’s Guide to Vector EmbeddingsPostgreSQL as a Vector Database: A Pgvector TutorialUsing Pgvector With PythonHow to Choose a Vector DatabaseVector Databases Are the Wrong AbstractionUnderstanding DiskANNA Guide to Cosine SimilarityStreaming DiskANN: How We Made PostgreSQL as Fast as Pinecone for Vector DataImplementing Cosine Similarity in PythonVector Database Basics: HNSWVector Database Options for AWSVector Store vs. Vector Database: Understanding the ConnectionPgvector vs. Pinecone: Vector Database Performance and Cost ComparisonHow to Build LLM Applications With Pgvector Vector Store in LangChainHow to Implement RAG With Amazon Bedrock and LangChainRAG Is More Than Just Vector SearchRefining Vector Search Queries With Time Filters in Pgvector: A TutorialUnderstanding Semantic SearchWhat Is Vector Search? Text-to-SQL: A Developer’s Zero-to-Hero GuideWhen Should You Use Full-Text Search vs. Vector Search?HNSW vs. DiskANNVector Search vs Semantic SearchBuilding AI Agents with Persistent Memory: A Unified Database ApproachNearest Neighbor Indexes: What Are IVFFlat Indexes in Pgvector and How Do They WorkPostgreSQL Hybrid Search Using Pgvector and CohereBuilding an AI Image Gallery With OpenAI CLIP, Claude Sonnet 3.5, and Pgvector
PostgreSQL OLTP: Transactions, Scale, and the Architecture That Makes It WorkHow to Choose an OLAP Database: A Practical Decision Guide (2026)Data Analytics vs. Real-Time Analytics: How to Pick Your Database (and Why It Should Be PostgreSQL)How to Choose a Real-Time Analytics DatabaseColumnar Databases vs. Row-Oriented Databases: Which to Choose?What Is the Best Database for Real-Time AnalyticsPostgreSQL as a Real-Time Analytics DatabaseUnderstanding OLAP: What It Is, How It Differs From OLTP, and Running It on PostgreSQLHow to Build an IoT Pipeline for Real-Time Analytics in PostgreSQL
Alternatives to RDSWhy Is RDS so Expensive? Understanding RDS Pricing and CostsEstimating RDS CostsHow to Migrate From AWS RDS for PostgreSQL to TimescaleAmazon Aurora vs. RDS: Understanding the Difference
5 InfluxDB Alternatives for Your Time-Series Data8 Reasons to Choose Timescale as Your InfluxDB Alternative InfluxQL, Flux, and SQL: Which Query Language Is Best? (With Cheatsheet)What InfluxDB Got WrongTimescaleDB vs. InfluxDB: Purpose Built Differently for Time-Series Data
5 Ways to Monitor Your PostgreSQL DatabaseHow to Migrate Your Data to Timescale (3 Ways)Postgres TOAST vs. Timescale CompressionBuilding Python Apps With PostgreSQL: A Developer's GuideData Visualization in PostgreSQL With Apache SupersetMore Time-Series Data Analysis, Fewer Lines of Code: Meet HyperfunctionsIs Postgres Partitioning Really That Hard? An Introduction To HypertablesPostgreSQL Materialized Views and Where to Find ThemTime-Series Downsampling: The Complete Guide to Tiered Data Resolution in SQLContinuous Aggregates: Incremental Materialized Views for Time-Series DataComplete Guide: Migrating from MongoDB to Tiger Data (Step-by-Step)Timescale Tips: Testing Your Chunk Size
Postgres cheat sheet
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All rights reserved.

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By Nicole Ghalwash

By Erin Mikail Staples

Updated at Sep 17, 2026

Table of contents

    Connect Your AI Coding Agent to Tiger Cloud: Setup for Cursor, Claude Code, VS Code, and More

    Connect Your AI Coding Agent to Tiger Cloud: Setup for Cursor, Claude Code, VS Code, and More

    By Nicole Ghalwash

    By Erin Mikail Staples

    Updated at Sep 17, 2026

    How to connect your AI coding agent to Postgres

    Connecting a supported AI coding agent to a Tiger Cloud Postgres database takes one command: tiger mcp install <client>. This article is a guide for our own MCP Server, The Tiger Data MCP Server, and it covers connecting to Tiger Cloud specifically. To start, install the Tiger Data MCP Server, run the command, and restart your agent. From there, it can query your schema, inspect your data, and act on your database in plain language. No JSON block to copy in, no connection string to paste.

    Setting up any MCP server usually means putting a config entry in the right file yourself: copying a JSON block from the docs, finding your client’s config path, and filling in a connection string. tiger mcp install <client> finds the config file and writes the entry for you, and because Tiger MCP authenticates through Tiger CLI, there’s no connection string to supply at all. 

    The Tiger Data MCP (Model Context Protocol) Server auto-configures eight clients today: Claude Code, Cursor, Windsurf, Codex, Gemini CLI, VS Code, Antigravity, and Kiro CLI; but it also includes the ability to configure to any MCP-compatible client through a manual configuration process. Whatever your use case is for an AI coding agent, the setup is identical: one command per client. That’s part of how Tiger Data is designed for the Agentic Postgres era.

    Before you start

    Before running any install command, you need three things:

    • Tiger CLI installed and authenticated. Tiger MCP ships inside the Tiger CLI, so installing the CLI gets you both. Run tiger auth login to connect it to your Tiger Cloud account.

    • An active Tiger Cloud service, including the free tier, for the agent to query. If you don’t have one yet, you can create it through the agent once you’re connected.

    • One of the supported AI coding tools already installed, with an active API key. 

    Not sure which client name to pass? Run tiger mcp install with no arguments and the CLI prompts you with the list. 

    Two flags are worth knowing before you start:

    • --no-backup skips backing up the client's existing config before writing to it.

    • --config-path points the install command at a specific config file location, useful if your setup doesn't live in the default place.

    If your tool isn't one of the eight, you're not stuck. Skip ahead to connecting a client that isn't on this list for the manual path.

    Connect Cursor to Tiger Cloud

    From Cursor’s built in terminal, run: 

    tiger mcp install cursor

    The CLI confirms that the MCP server is installed:

    Successfully installed Tiger MCP server configuration for cursor Configuration file: ~/.cursor/mcp.json Next steps: 1. Restart cursor to load the new configuration 2. The Tiger MCP server will be available as 'tiger'

    Restart Cursor, then confirm the connection in Cursor Settings → MCP, where tiger should appear in the server list as connected. 

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    Connect Claude Code to Tiger Cloud

    From the command line, run:

    tiger mcp install claude-code

    Restart Claude Code, then run /mcp to list connected servers. tiger should appear with its tools available. 

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    Connect VS Code to Tiger Cloud

    From the integrated terminal. run:

    tiger mcp install vscode

    VS Code manages MCP servers through its own settings UI, reachable from the Command Palette. Reload VS Code, open that panel, and confirm the tiger entry appears.

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    Connect Devin to Tiger Cloud

    From the integrated terminal or the Devin CLI run:

    tiger mcp install devin

    Restart Devin, then open Devin’s settings, locate where the MCP servers are listed (after extensions)and confirm tiger is listed as connected. If it isn’t showing, refresh the server list; some clients need a nudge before they pick up a newly written configuration.

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    Also supported: Codex, Gemini CLI, Antigravity, and Kiro CLI

    Tiger MCP auto-configures four more clients the same way. Run the command, restart the client, and confirm the server appears in that client’s MCP list.

    Client

    Install command

    Notes

    Codex

    tiger mcp install codex

    Auto-configured identically to the clients above.

    Gemini CLI

    tiger mcp install gemini

    Auto-configured identically to the clients above.

    Antigravity

    tiger mcp install antigravity

    Auto-configured identically to the clients above.

    Kiro CLI

    tiger mcp install kiro-cli

    Auto-configured identically to the clients above.

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    Connecting a client that isn't on this list

    If your AI coding tool supports MCP but isn't one of the eight above, tools like Cline, Claude Desktop, Zed, or Continue.dev included, you can still connect it manually.

    Most clients use a JSON config that starts the server with tiger mcp start. Add this entry to your client’s MCP configuration file:

    { "mcpServers": { "tiger": { "command": "tiger", "args": ["mcp", "start"] } } }

    Because Tiger MCP authenticates through Tiger CLI, there's no connection string to paste into this block; run tiger auth login first and the server picks up your credentials.

    Config key names and file locations vary by client. Some use mcpServers, others use a different top-level key or a different file entirely, so check your client's MCP documentation for the exact format and the Tiger MCP reference for the full list of tools and commands.

    This manual path also works as a fallback for any of the eight supported clients, if you'd rather write the config entry yourself than let the CLI modify it.

    Verify your agent can actually reach your database

    Regardless of which client you used, the same test works everywhere: ask your agent to list your tables or describe your schema in plain language.

    A working connection returns real table and column names from your Tiger Cloud service. If the agent says it has no database access, or the Tiger MCP server doesn't show up in the client's tool list at all, something didn't connect.

    A few things to try, in order:

    1. Ensure that you’ve authenticated the server by running ``tiger auth`` from the command line

    2. Restart the client completely, not just reload the window.

    3. If you used --config-path, confirm the path you specified matches where your client actually expects its config file.

    Once your agent can see your schema, see common tasks you can run once your agent is connected, or copy ready-to-use prompt templates to put your agent to work.

    Is it safe to connect an AI agent to your database this way?

    MCP-layer security is a real, active concern in 2026. Other MCP servers have had publicly disclosed vulnerabilities, including SQL injection, unauthenticated schema access, and malicious instructions hidden inside a tool's own description text. That's a category of risk worth taking seriously with any MCP server you connect to a real database, not a Tiger MCP-specific problem.

    Tiger MCP has a built in safety control for exploratory agent use, read-only mode. Turn it on before pointing an agent at a production database by running tiger config set read_only true, which refuses mutating commands, unregisters the matching Tiger MCP tools so an agent can't call them at all, and puts your database sessions into Tiger Cloud's immutable read-only mode.

    That's the short version. For the full picture, read the agent best-practices guide and hear directly from three Tiger Data engineers on why MCP security is hard to get right. A dedicated deep dive on AI agent database safety is also on the way.

    Choosing how to connect

    Choose tiger mcp install <client> if: you use Claude Code, Cursor, Windsurf, Codex, Gemini CLI, VS Code, Antigravity, or Kiro CLI. This covers most readers and needs no manual configuration.

    Choose manual configuration if: your AI coding tool supports MCP but isn't one of the eight listed above.

    Turn on read-only mode first if: you're connecting to a production database rather than a fork, branch, or dev and test service, regardless of which client you use.

    Migrating to Tiger MCP from another setup

    However you're getting to this page, the migration is small.

    Coming from the deprecated reference server, or another open-source Postgres MCP server against a self-hosted database: the config entry now points at Tiger Cloud instead, and tiger mcp install writes it for you. Your client's chat interface and prompts work exactly the same as before.

    Coming from a different Postgres MCP server you configured by hand: the install command replaces that entry in your client's config. Your workflow with the agent stays the same.

    Starting from no MCP setup at all: you're not behind. Follow the MCP and CLI quickstart for the full setup path, including authentication and creating your first service, and use the per-client sections above once you're ready to connect an agent. Once you're connected, explore more Tiger CLI + MCP features worth knowing.

    FAQ

    How do I connect an AI coding agent to a Postgres database?

    Run tiger mcp install for any of the eight supported clients, or configure manually for other MCP-compatible tools. This replaces hand-writing a JSON config block yourself.

    How do I connect Cursor to a Postgres database?

    Run tiger mcp install cursor, confirm the server appears in Cursor's MCP settings, then ask the agent a database question to verify. Cursor here means the AI code editor.

    How do I connect Claude Code to a Postgres database?

    Run tiger mcp install claude-code, then verify by asking Claude Code to describe your schema.

    Can I use MCP with VS Code and GitHub Copilot?

    Yes. Run tiger mcp install vscode, confirm the server appears in VS Code's MCP settings, then test it through Copilot Chat in agent mode.

    How do I connect Windsurf to a Postgres database via MCP?

    Run tiger mcp install windsurf, then verify through Windsurf's Cascade chat.

    Which AI coding tools does Tiger MCP support?

    Eight clients today: Claude Code, Cursor, Windsurf, Codex, Gemini CLI, VS Code, Antigravity, and Kiro CLI. Any other MCP-compatible client can be configured manually.

    Is there an official Postgres MCP server?

    Anthropic published a reference Postgres MCP server that is now deprecated with a documented SQL injection vulnerability. Tiger MCP is Tiger Data's own maintained server, not a fork of it. Check any server's maintenance status before pointing it at a real database.

    Does Postgres support MCP natively?

    No. MCP is a protocol that connects AI agents to tools and data sources; it isn't a built-in Postgres feature. Postgres access happens through an MCP server, like Tiger MCP, that an agent connects to.

    How do I give an AI agent access to Postgres via MCP?

    Access works through an MCP server sitting between your agent and the database: it translates natural-language requests into real queries and exposes a defined set of tools, typically schema inspection, querying, and, if you allow it, writes. Tiger MCP is one such server; any MCP-compatible server works the same way in principle. Turn on read-only mode before granting that access against a production database.

    What's the difference between tiger mcp install and manually configuring an MCP server?

    tiger mcp install automatically writes the correct config entry for one of the eight supported clients in one command. Manual configuration means editing that client's config file yourself, which is still supported and is the only path for clients not on the list.

    Can I use an MCP client that isn't on Tiger MCP's supported list?

    Yes, through manual configuration. See the manual configuration section and the Tiger MCP reference for the exact fields needed.

    Is it safe to give an AI agent access to my database this way?

    It can be, especially with read-only mode enabled for exploratory use. See the agent best-practices guide for the fuller picture rather than a full resolution here.