--- title: "Postgres for Sensor and Machine Data on AWS" description: "Run Tiger Cloud on AWS to ingest, store, and query sensor and machine data at scale. Time-series analytics on Postgres — no rewrite, no second system." url: "https://www.tigerdata.com/partners/aws" --- # Postgres for sensor and machine data on AWS Industrial, energy, and robotics systems push relentless streams of sensor and time-series data. Tiger Cloud runs on AWS and extends Postgres to ingest, compress, and query it at scale, so your telemetry lives in one database instead of a sprawl of pipelines. - Built for IoT - PAYGO or annual commit - Counts toward AWS EDP / PPA spend ### Better together: Your data stays on AWS **ingest / stream** — High-throughput sensor and machine data, from edge to cloud ↓ **Tiger cloud on AWS** — Postgres + Hypertables + Hypercore + Continuous Aggregates **Tiered storage** — Cold data on S3 — compressed, still queryable in SQL **Tiger lake** — Apache Iceberg on S3 Tables ↓ **Analyze** — BI, dashboards & alerting **ML / AI** — Model training and Inference ## Trusted by thousands of companies in IoT, running on AWS - Toyota - Schneider Electric - [Flogistix](https://www.tigerdata.com/blog/how-flogistix-by-flowco-reduced-infrastructure-management-costs-by-66-with-tiger-data) - Glooko - Speedcast - Speedscale - MarketReader - Octave Energy - Torus - Cactos ## Why Tiger Data + AWS One database for live data, on the cloud you already run The most cost-effective system is the one you don't have to build, sync, and operate. Tiger Cloud adds time-series analytics to Postgres inside AWS, so analytics stays on your source of truth instead of moving to a second system. ### No new query language, no rewrite _Stay on Postgres_ Tiger Cloud is Postgres extended, not replaced. Keep your SQL, drivers, and existing AWS tooling. Adoption is a connection string, not a migration project. ### Ingest, store, and analyze in one place _Runs on your AWS stack_ Stream from MSK, Kinesis, and IoT Core. Tier cold data to Amazon S3 and still query it in SQL. Connect to SageMaker and Bedrock without leaving AWS. ### Procurement you already have _Buy through Marketplace_ Spend counts towards AWS EDP or PPA commitment, ensuring you use budget that's already allocated. ### Fewer systems, less on-call _Consolidate & cut cost_ Native compression up to 95% keeps more history online for less. Teams routinely fold a separate analytics database back into one Postgres on AWS. ## Wired into the AWS services your team already uses Tiger Cloud connects across the AWS data path, from ingest and streaming through storage, compute, and analytics. ### ingest & streaming - Amazon MSK - AWS IoT Core - Amazon Kinesis ### storage - Amazon S3 Tiered storage - Amazon Kinesis - AWS IoT Core ### compute & ml - Amazon EC2 - Amazon SageMaker - Amazon EKS - Amazon Bedrock ### databases - Amazon RDS - Amazon Redshift - Amazon Aurora ### analytics & query - Amazon Athena - Amazon CloudWatch - Amazon Quick ### networking - AWS PrivateLink ## Ask questions of your energy data in plain language Connect Amazon Quick to your operational data in TimescaleDB through Model Context Protocol (MCP). Watch how energy teams can use conversational AI to explore their data, with demos for oil and gas and power and utilities. ### oil & gas See how Amazon Quick connects to TimescaleDB to explore oilfield services data through natural-language questions. With **Anton Umnikov**, Solutions Architect, Tiger Data ### power and utilities Explore the Tiger Data and Amazon Quick integration using a power and utilities dataset. With **Valerie Parham-Thompson**, Solutions Architect, Tiger Data ## Leave Timestream. Stay on AWS. On June 20, 2025, AWS closed Amazon Timestream for LiveAnalytics to new customers and now points them to Timestream for InfluxDB. That path means learning a new query language and running a different engine. Tiger Cloud keeps you on Postgres and standard SQL, on AWS, with hypertables and compression built for the same high-ingest, high-cardinality workloads Timestream handled. - Postgres and standard SQL, not Flux or InfluxQL - Hypertables and compression up to 95% for high-ingest telemetry - Query raw, in SQL - Stay inside AWS: buy on Marketplace, tier cold data to Amazon S3 [Read the migration guide](https://www.tigerdata.com/blog/so-long-timestream-how-and-why-to-migrate-before-its-too-late) > We were sitting at about 800 milliseconds on average for our response time with Timestream, and switching over to Timescale we’re now like 70 milliseconds. We thought we would need a bigger instance to run our production, but we’re just running it on one CPU and it’s cruising. — **engineer**, Torus (migrated from Amazon Timestream) ## Move workloads stranded at the edge into AWS Factories, substations, and remote sites generate years of sensor and machine data that rarely makes it past a local server. Run TimescaleDB at the edge and on-prem, then let Cloud Sync stream it into Tiger Cloud on AWS. Local site data becomes fleet-wide visibility, without ripping out what already works on the plant floor. 1. **Edge** — Sensors and PLCs captured by your SCADA gateway or edge platform. 2. **Site** — TimescaleDB Enterprise on-premises. SQL-native. Air-gap ready. 3. **Cloud** — Tiger Cloud on AWS. Fleet-wide analytics and multi-site visibility via Cloud Sync. 4. **Lakehouse** — Apache Iceberg on Amazon S3, or Snowflake and Databricks, via Tiger Lake. ## Teams run demanding workloads on Tiger Data and AWS > The end result was excellent. Ingestion is faster than before, costs are lower than before, and we ended up ahead of our original timeline. — **Per Grapatin**, VP of Engineering, Glooko ([Read more](https://www.tigerdata.com/blog/how-glooko-turns-3b-data-points-per-month-into-lifesaving-diabetes-healthcare-tiger-data)) _480x faster_ - **55%** LOWER COST - **35%** LOWER AWS COSTS ([Read more](https://www.tigerdata.com/case-studies/speedscale)) - **20GB** Data Ingested per hour ([Read more](https://www.tigerdata.com/blog/how-speedcast-built-a-global-communications-network-on-tiger-lake)) - **66%** LOWER COSTS ([Read more](https://www.tigerdata.com/blog/how-flogistix-by-flowco-reduced-infrastructure-management-costs-by-66-with-tiger-data)) > The biggest benefit of Tiger Data is that it gives us first-class time series analytics while staying on Postgres. — **Web Begole**, CTO & Co-founder, MarketReader ([Read more](https://www.tigerdata.com/blog/how-marketreader-processes-3m-trades-min-deliver-us-market-trading-insights-timescaledb)) _3M TRADES/MIN_ ## Start in minutes with budget you already have Subscribe through AWS Marketplace and your spend counts toward your AWS EDP or PPA committed spend. _4.6 / 5 on AWS Marketplace · 33 reviews_ ### Pay as you go Usage-based pricing with independent compute and storage scaling. Start on a 30-day free trial and only pay for what you run. [Subscribe](https://aws.amazon.com/marketplace/pp/prodview-iestawpo5ihca?sr=0-1&ref_=beagle&applicationId=AWSMPContessa) ### Annual Commit Commit annually for predictable pricing on production workloads, billed through AWS and counting toward your committed spend. [Subscribe](https://aws.amazon.com/marketplace/pp/prodview-ezxwlmjyr6x4u) ## Keep your time-series data on Postgres + AWS. Add the analytics. Spin up Tiger Cloud on a 30-day free trial, or subscribe through AWS Marketplace in minutes. [Start a free trial](https://www.tigerdata.com/go/trial) · [Subscribe on the AWS Marketplace](https://aws.amazon.com/marketplace/pp/prodview-iestawpo5ihca?sr=0-1&ref_=beagle&applicationId=AWSMPContessa)