An open source time-series SQL database optimized for
fast ingest and complex queries, powered by PostgreSQL.
TimescaleDB provides the best possible experience when working with time-series data with the power and convenience of SQL. Built on PostgreSQL and proven for mission critical workloads in the most demanding environments, TimescaleDB provides a familiar operational experience and works with any tool in the rich and vibrant PostgreSQL ecosystem.
Because of these characteristics and built-in time-series analytical features, TimescaleDB increases developer productivity and optimizes resource efficiency, all while minimizing operational costs. And now with distributed operation across many servers, TimescaleDB scales to your ingest, query, and storage needs.
The ability to ingest massive amounts of data at scale is a critical component to working with time-series data. TimescaleDB achieves a much higher and more stable ingest rate for time-series data by using automated time-space partitioning. This means that all writes to recent time intervals are only to data chunks that remain in memory, and all indexing also stays local in memory. Yet this complexity is invisible to users, who see only a single hypertable for all their data. TimescaleDB allows users to write millions of data points per second with a single machine, or even tens of millions per second using its distributed hypertable transparently spread over many servers.
TimescaleDB provides a hypertable abstraction layer on top of your time-series data for more efficient storage. A hypertable is structured especially for chunks (data partitioned into many individual tables), while still looking, feeling, and acting just like a normal SQL table. Virtually all user interactions with TimescaleDB are with hypertables. Creating tables and indexes, altering tables, inserting data, selecting data, etc. can (and should) all be executed on the hypertable, and this simple abstraction persists even for distributed hypertables.. And with its best-in-class type-specific native compression, TimescaleDB’s storage is highly efficient, offering 90-95% storage savings. Users can store 100s of billions of rows and 10s of terabytes of data on a single machine, or scale to petabytes across many servers.
TimescaleDB includes a number of time-oriented features that aren't found in traditional relational databases including functions for time-oriented analytics. These analytics provide a way to map irregular raw data to fixed time-intervals. For example, users can employ functions to write complex windowing, gap-filling, interpolation, and last-observation-carried-forward (LOCF) queries.
And, because TimescaleDB is built atop a PostgreSQL foundation, you can store your business data in the same relational database as your time series data, giving you a full view of your business and customers with a simple JOIN.
TimescaleDB also provides certain data management capabilities that are not readily available in traditional relational databases. These include data retention, downsampling, native compression, data tiering, hypertable and schema management, data lifecycle management, and more.. Users can create policies to continuously aggregate data, building automated rollups that can be queried for higher performance, and data retention policies can then downsample so only aggregates are retained after certain time periods. We also offer the opportunity to automate many of these capabilities for simplified operations.
Timescale Cloud has options for every cloud platform provider. Choose the compute and storage confgurations based on your needs.
If you want to deploy and manage TimescaleDB in your own environment,
Timescale Community Edition is free.
TimescaleDB is the only open source time-series database that supports full SQL. Optimized for fast ingest and complex queries, TimescaleDB is easy to use like a traditional relational database, yet scales in ways previously reserved for NoSQL databases. In particular, this makes TimescaleDB an ideal candidate for operational analytics. TimescaleDB Open Source is distributed under the Apache 2.0 license.
TimescaleDB is ideal for time-series workloads that would benefit from a SQL interface. SQL carries a variety of benefits: a query language that most developers already know; rich set of functions and utilities; and a broad ecosystem of tools, connectors, and visualization options. Also, since SQL JOINS are natively supported in TimescaleDB, data from different sources can be combined at query time (e.g., combining relational data stored in PostgreSQL tables with time-series data stored in TimescaleDB hypertables). This ability to store relational data alongside time-series data enables developers to simplify their stack, potentially reducing complex polyglot architectures to a single operational analytical database.
Owing to these advantages, TimescaleDB is currently deployed across a variety of industries, including manufacturing, energy, utilities, mining, oil and gas, finance, ad tech, smart spaces, and more. Use cases include complex monitoring and analytics; predicting the performance and behavior of applications, models, consumers and connected machines; powering operational analytical workflows and dashboards; for QA and performance testing
Read our TimescaleDB-PostgreSQL benchmarks:
To summarize, TimescaleDB offers:
TimescaleDB comes in three flavors:
Timescale is our company. We build a category-defining time series database called TimescaleDB. We host and manage TimescaleDB on behalf of our customers via a product we call Timescale Cloud.
We currently support installation packages for Docker, Ubuntu, Debian, RHEL/CentOS, Windows, Azure, MacOS, and Amazon Machine Instance
We can provision your Timescale Cloud instances in Amazon Web Services, Microsoft Azure, or Google Cloud Platform.
Timescale Cloud manages all of the operational elements of your database so you can focus on building your applications and not making sure the infrastructure works. We ensure you have a secure, high availability environment where we manage the infrastructure all the way down to setting up replications, point-in-time recovery, read replicas, backups, and more.
Both the open-source and Community editions of TimescaleDB are free to use in both production and test/development environments.
The cost of Timescale Cloud depends on your cloud provider, the region you select, and the compute and storage capacity you require. You can use the Pricing Calculator to get an idea of how much Timescale Cloud will cost, based on your preferences and needs.
There are no limits to the amount of data you can store in Timescale Cloud. A single instance of Timescale offers 10TB of disk in our largest plan, but you can provision additional instances easily and anytime. With our native compression, you're able to get much more storage out a single instance as well - with many users frequently seeing 20x compression.
If you’re interested in learning more or need help, we suggest one (or all!) of the below:
See more frequently asked questions in the Timescale documentation.