TimescaleDB

An open source time-series SQL database optimized for
fast ingest and complex queries, powered by PostgreSQL.

TimescaleDB Products
HostedTimescale Cloud
Hosted and fully-managed TimescaleDB deployments in the cloud of your choice
SoftwareCommunity
Leading time-series database optimized for advanced analytics and built for production use cases.
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Looking for the open source version? Visit GitHub

How TimescaleDB works

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.

Overview

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.

Ingest

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.

Store

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.

Analyze

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.

Manage

Which Timescale version is right for you?

Timescale Cloud

Time-series analytics
Hypertable abstraction layer
Automatic chunking / partitioning
Optimized time-based constraint exclusion
Joins across time-series and relational tables
Built-in flexible time bucketing
Advanced analytical functions<br/>(gapfilling, LOCF, interpolation)
Automatic continuous aggregations
Data lifecycle management
Efficient data retention capabilities
Chunk-level data reordering on disk
Automated data retention policies
Native data compression
Data tiering with plugable storage configurations
Enterprise capabilities
High availability
Backup / restore
Support for Kubernetes
Role-based access control
Support for the PostgreSQL deployment ecosystem
Operations & infrastructure
Managed by Timescale
Deployment
Managed by Timescale
Administration
Automated Backups and Maintenance
Visualization tooling (Grafana)
Support and services
Slack
Support level †
License

Community

Time-series analytics
Hypertable abstraction layer
Automatic chunking / partitioning
Optimized time-based constraint exclusion
Joins across time-series and relational tables
Built-in flexible time bucketing
Advanced analytical functions<br/>(gapfilling, LOCF, interpolation)
Automatic continuous aggregations
Data lifecycle management
Efficient data retention capabilities
Chunk-level data reordering on disk
Automated data retention policies
Native data compression
Data tiering with plugable storage configurations
Enterprise capabilities
High availability
Backup / restore
Support for Kubernetes
Role-based access control
Support for the PostgreSQL deployment ecosystem
Operations & infrastructure
Any on-premise, public, or private cloud infrastructure
Deployment
Managed by customer
Administration
Support and services
Slack
Support level †
License

Open Source

Time-series analytics
Hypertable abstraction layer
Automatic chunking / partitioning
Optimized time-based constraint exclusion
Joins across time-series and relational tables
Built-in flexible time bucketing
Data lifecycle management
Efficient data retention capabilities
Enterprise capabilities
High availability
Backup / restore
Support for Kubernetes
Role-based access control
Support for the PostgreSQL deployment ecosystem
Operations & infrastructure
Any on-premise, public, or private cloud infrastructure
Deployment
Managed by customer
Administration
Support and services
Slack
Support level †
License

Which Timescale version is right for you?

You can choose to deploy on any on premise, public, or private cloud infrastructure. Or you can sign up for Timescale Cloud which is hosted and fully-managed in the cloud provider of your choice.
Timescale Cloud
Community
Open-source
Time-series analytics
Hypertable abstraction layer
Perform all interactions with hypertables which look and feel just like PostgreSQL tables. The hypertable abstraction layer on top of your time-series data allows for more efficient storage.
Automatic chunking / partitioning
All of the complexities associated with partitioning your chunks is performed automatically for you behind a hypertable.
Optimized time-based constraint exclusion
Supports all standard PostgreSQL constraint types and allows for constraint exclusion to take place at exclusion time for faster query performance.
Joins across time-series and relational tables
JOINs allow you to combine all types of data within one unified system.
Built-in flexible time bucketing
A more powerful version of the standard date_trunc function, it allows for arbitrary time intervals, as well as flexible groupings and offsets, instead of just second, minute, hour, etc.
Advanced analytical functions
(gapfilling, LOCF, interpolation)
These features allow you to quickly fill in missing gaps of data which is useful for visualization.
Automatic continuous aggregations
This feature allows you to speed up queries that aggregate over time by automatically calculating the query in the background and materializing the results.
Data lifecycle management
Efficient data retention capabilities
TimescaleDB allows efficient deletion of old data at the chunk level using the drop_chunks function.
Chunk-level data reordering on disk
Reorder a chunk data on disk to match an index. Reduce query times for common queries.
Automated data retention policies
A database administrator can create, remove, or alter policies that cause drop_chunks to be automatically executed according to some defined schedule.
Native data compression
Up to 96% compression ratios for time-series workloads.
Data tiering with plugable storage configurations
As data ages, you can change the type of storage it resides on by adding new tablespaces backed by different classes of storage.
Enterprise capabilities
High availability
TimescaleDB supports PostgreSQL’s built-in streaming replication for high-availability.
Backup / restore
TimescaleDB inherits PostgreSQL’s backup functionality. You can choose to do a physical backup or logical backup with pg_dump and pg_restore.
Support for Kubernetes
Use TimescaleDB's Helm Charts for easy configuration.
Role-based access control
Administer and control security policies.
Support for the PostgreSQL deployment ecosystem
If it works with PostgreSQL, it will work with TimescaleDB!
Operations & infrastructure
Deployment
Managed by Timescale
Any on-premise, public, or private cloud infrastructure
Administration
Managed by Timescale
Managed by customer
Automated Backups and Maintenance
Visualization tooling (Grafana)
Support and services
Support level †
Slack
Slack
Slack
† Free Community Support is available for all offerings. Learn more about Timescale Subscriptions.

Timescale Cloud Pricing Calculator

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.

  • Choose your 
    cloud
    Choose a cloud provider to run your TimescaleDB service instance.
  • Select cloud region
  • Select a plan
  • Choose Configuration
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Dev
  • Small footprint
  • 1 day PITR
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Basic
  • Fully managed backups
  • 2 days PITR
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Pro
  • High availability
  • Fully managed backups
  • 3 days PITR
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Dev Only
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I/O Optimized
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Compute Optimized
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Storage Optimized
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Take advantage of the convenience and reliability of Timescale Cloud

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Estimated price
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0
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Frequently asked questions

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:

  • Ease-of-use: TimescaleDB is far easier to use because creating partitions (or what we call "chunks") is automatically performed for the user. All of the complexity of automatic partitioning is abstracted away behind a "hypertable", which users interact with just as they would with a PostgreSQL table.
  • Much higher ingest scale: TimescaleDB sees throughput more than 20X that of PostgreSQL once tables reach moderate size (e.g., 10s of millions of rows). While vanilla PostgreSQL is suitable for time-series data at low volumes, it does not scale well to the volume of data that most time-series applications produce, especially when running on a single server. In particular, vanilla PostgreSQL has poor write performance for moderate tables, and this problem only becomes worse over time as data volume grows linearly in time. These problems emerge when table indexes can no longer fit in memory, as each insert will translate to many disk fetches to swap in portions of the indexes' B-Trees. TimescaleDB solves this through its heavy utilization of time-space partitioning, even when running on a single machine. So all writes to recent time intervals are only to tables that remain in memory, and updating any secondary indexes is also fast as a result.
  • Superior (or similar) query performance: Queries that can reason specifically about time ordering can be much more performant (1000s of times faster) in TimescaleDB. On single disk machines, at least, many simple queries that just perform indexed lookups or table scans are similarly performant between PostgreSQL and TimescaleDB.
  • Much faster data deletion: To save space or to implement data retention policies, vanilla PostgreSQL requires expensive "vacuuming" operations to defragment the disk storage associated with such tables. TimescaleDB avoids vacuuming operations and easily enforces data retention policies by specifying the data you wish to be deleted that is older than a specified time period. For more information, see Data Retention.
  • Extended time-oriented features: TimescaleDB includes time-series specific features not included in vanilla PostgreSQL and entirely unique to TimescaleDB (e.g., time_bucket,first and last), with more to come.

TimescaleDB comes in three flavors:

  • The open source version of TimescaleDB can be cloned from our GitHub repository and built locally. It’s free to use.
  • TimescaleDB Community can be installed on a number of operating system environments, or cloned from our GitHub repository and built locally. It’s free to use.
  • Timescale Cloud is TimescaleDB hosted and managed by Timescale. You can sign up for a free trial (comes with $300 in free credits).

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.

The open source and Community editions of TimescaleDB are free to use in test or deployment 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:

  • Join our public Slack developer community to ask questions, meet other community members, and get help from our technical team.
  • Email our support team ([email protected]) to report issues or bugs. You can also reach us on Slack.
    • If you’re using TimescaleDB Community or open source, we suggest reporting issues via GitHub directly.
  • Subscribe to the Timescale Newsletter and Release Notes to get new content, demos, and the latest information on product launches and feature updates.

See more frequently asked questions in the Timescale documentation.

Getting started
1
Sign up for Timescale Cloud
Timescale Cloud is the easiest and fastest way to get started with time-series data.
Start free Timescale Cloud trial
2
Explore docs
Explore the Timescale documentation to learn how to use TimescaleDB’s built-in features and get tutorials, data sets, and more.
View documentation
3
Get familiar with Timescale
Follow this tutorial to get first-hand experience using all of TimescaleDB’s functionality.
Start tutorial
4
Join us on Slack
We have an active Community Slack, and our engineers regularly answer questions and share updates.
Connect on Slack
5
Subscribe to Timescale Newsletter
Stay up to date on all the latest content, demos, events, and new product developments.
Sign up for updates