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PostgreSQL ++ for time series and events

Engineered to handle demanding workloads, like time series, vector, events, and analytics data. Built on PostgreSQL, with expert support at no extra charge.

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“Our queries are really fast, taking only 100 ms for a table with around 1.4 billion rows.”

Christian Halim, engineering manager at Pintu, one of Indonesia’s leading cryptocurrency trading platforms, explains how his team inserts 5 million data rows every 30 minutes, queries more than a billion data rows in 0.1 seconds, and automatically deletes a billion data rows per day.

Your engine for blazingly fast application data

Built for price-performance

Speed, Scale, and Savings

Blazing-fast query speed

Up to 1000x faster queries than vanilla PostgreSQL, AWS Timestream, InfluxDB, and MongoDB. Give your users answers in milliseconds, not minutes.

Without breaking the bank

Pay only for what you store. Get 5x storage savings via columnar compression. Don’t worry about extra charges for reads, writes, or other hidden costs.

At infinite scale

Flexible scaling with independent compute and storage. Do more with less resources via database optimizations. Tier data into object storage for low-cost infinite scalability.

A smoother route from MVP to GA

Build faster

WITH setup AS (SELECT lag(temperature) OVER (PARTITION BY freezer_idORDER BY ts) as prev_temp,extract('epoch' FROM ts) as ts_e,extract('epoch' FR OM lag(ts) OVER (PARTITION BYfreezer_id ORDER BY ts)) as prev_ts_e,*FROM freezer_temps),nextstep AS (SELECT CASE WHEN prev_temp is NULL THEN NULLELSE (prev_temp + temperature) / 2 * (ts_e - prev_ts_e)END as weighted_sum,*FROM setup)SELECT freezer_id,avg(temperature),sum(weighted_sum) / (max(ts_e) - min(ts_e)) astime_weighted_averageFROM next stepGROUP BY freezer_id;SELECT freezer_id,AVG(temperature),average(time_weight('Linear', ts, temperature))AS time_weighted_averageFROM freezer_tempsGROUP BY freezer_id;

Prototype in days not weeks

Out-of-the-box productivity with purpose-built time-series features like policies for automated data aggregation, downsampling, and retention.

Using the skills you already have

Full SQL and more than 100 ready-to-go hyperfunctions to speed up complex data analysis without leaving your time-series database.

With your existing cloud-native infrastructure

Programmatic APIs and VPC Peering to safely integrate with your cloud infrastructure. Monitor with Datadog and CloudWatch. Leverage AWS Lambda, AWS IoT, AWS Kinesis, and more.

Focus on your application, not your database

Worry free and easy

High availabilityAutomatic backups

Leave DBOps to us

We give you back engineering time by taking care of database tuning, continuous backups and failover, automated database upgrades, security and encryption, compliance—like SOC2 and GDPR—and all operational tasks.

Roll to prod and sleep soundly

Safely test changes with a forking workflow. Redundancy and replication across storage and Availability Zones. Integrated monitoring for DevOps. PITR for any mistakes along the way.

With free support standing by

Access to enterprise-level help via ticketing included with your Timescale subscription. Receive consultative advice from our global team of database engineers at no extra cost.

It’s PostgreSQL but better

PostgreSQL++

Get more from PostgreSQL

Scale PostgreSQL with automatic partitioning and indexing, incrementally-updated materialized views, columnar compression, and time-series hyperfunctions.

Without losing the good stuff

Keep using all the PostgreSQL features you love: data types, index types, CTEs, UDFs and more. 100% SQL. No learning curve. Seamless developer onboarding.

While using the tools you know

Leverage the entire PostgreSQL ecosystem of tools, drivers, and connectors. If it works with PostgreSQL, it works with Timescale.

Build the New Age of Computing

Join a community of 4.2M+ active Timescale databases (and counting).

Active databases

4,234,123

GitHub stars

14,309

G2 score

4.7

G2 score

Timescale's hyperfunctions significantly reduce our development time and continuous aggregates make it easier to do analysis on high volumes of data, plus with lower server costs.

Evert Van Cauwenberg

Jane.be, CTO

By choosing Timescale, we shaved off months from our minimum viable product development time. The advanced time-series features enable us to produce top-notch market data feeds.

Mikko Ohtamaa

Trading Strategy, CEO

Our experience using Timescale has been fantastic. We're really impressed with the core technical innovations, particularly around hypertables and compression.

Adam Inoue

Messari, Software Engineer

Timescale integrated seamlessly into our AWS data pipeline with AWS IoT Greengrass, AWS Kinesis, and AWS Lambda to help power our controlled environment agriculture platform.

Mark Thompson

Square Roots, Senior Infrastructure Engineer

Timescale's hyperfunctions significantly reduce our development time and continuous aggregates make it easier to do analysis on high volumes of data, plus with lower server costs.

Evert Van Cauwenberg

Jane.be, CTO

By choosing Timescale, we shaved off months from our minimum viable product development time. The advanced time-series features enable us to produce top-notch market data feeds.

Mikko Ohtamaa

Trading Strategy, CEO

Our experience using Timescale has been fantastic. We're really impressed with the core technical innovations, particularly around hypertables and compression.

Adam Inoue

Messari, Software Engineer

Timescale integrated seamlessly into our AWS data pipeline with AWS IoT Greengrass, AWS Kinesis, and AWS Lambda to help power our controlled environment agriculture platform.

Mark Thompson

Square Roots, Senior Infrastructure Engineer

Timescale's hyperfunctions significantly reduce our development time and continuous aggregates make it easier to do analysis on high volumes of data, plus with lower server costs.

Evert Van Cauwenberg

Jane.be, CTO

By choosing Timescale, we shaved off months from our minimum viable product development time. The advanced time-series features enable us to produce top-notch market data feeds.

Mikko Ohtamaa

Trading Strategy, CEO

Our experience using Timescale has been fantastic. We're really impressed with the core technical innovations, particularly around hypertables and compression.

Adam Inoue

Messari, Software Engineer

Timescale integrated seamlessly into our AWS data pipeline with AWS IoT Greengrass, AWS Kinesis, and AWS Lambda to help power our controlled environment agriculture platform.

Mark Thompson

Square Roots, Senior Infrastructure Engineer

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