TimescaleDB

Cloud
Hosted and fully‑managed options for TimescaleDB, designed for all your deployment and business needs.
Software
Leading relational database for time‑series, optimized for advanced analytics and built for production use cases.
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The Cloud Advantage

Worry-free operations

Hosted and managed by Timescale on your behalf.

Complete flexibility

Deploy in any major cloud provider in 75+ regions.

Get started quickly

Launch your first database in seconds. 
As low as $49/month.

Supercharged PostgreSQL

Rely on the same PostgreSQL you know and love, with full SQL, rock‑solid reliability, and the largest ecosystem of developer and management tools.

  • Full SQL, powerful analytics, no restrictions
  • Leverage your favorite PostgreSQL extensions
  • Entire toolset works: ORMs, connectors, JDBC, applications
  • Connect Prometheus for all your observability metrics
  • Visualize data using the dashboards you love
-- What’s the memory consumption for
-- each of my containers right now?
SELECT
  time_bucket('10 seconds', time) AS period,
  container_id, avg(free_mem), min(free_mem)
FROM metrics
WHERE time > NOW () - interval '10 minutes'
GROUP BY period, container_id
ORDER BY period DESC, container_id;

Accelerated performance

Achieve 10-100x faster queries than PostgreSQL, InfluxDB, and MongoDB. Leverage query parallelization, continuous aggregates, and other performance optimizations.

  • Achieve 10X faster inserts and ingest 1.5M+ more metrics per second per server for high-cardinality workloads
  • Optimized time-series queries and advanced time-series analytics
  • Real-time insights over automated continuous aggregations
  • Fast scans over compressed columnar storage
  • Query faster over longer time horizons with downsampling

Massive scale

Write millions of data points per second. Store 100s of terabytes on a single node or petabytes across multiple nodes. Handle high‑cardinality data easily.

  • Store 100s of billions of rows and 10s of TBs of data per server
  • Record billions of distinct time‑series, collect everything you need
  • Best‑of‑breed datatype‑specific compression for 16x storage capacity
  • Create distributed hypertables across many TimescaleDB nodes
  • Parallelize scans and aggregation queries across many nodes

Relational and time-series, together

Simplify your stack and store your relational data alongside time‑series data. Ask more complex queries, build more powerful applications faster.

  • Centralize storage of time‑series, application, and sensor data
  • Correlate metrics with business and system‑of‑record data
  • Unlimited metadata, don’t worry about cardinality of labels
  • Perform JOINs to understand relations with time‑series
  • Ensure clean, correct data with foreign keys and constraints

Worry-free operations

Let us run TimescaleDB for you, fully managed on AWS, Azure, or GCP in over 75 regions, with a top-rated support team to ensure your success.

  • Spin up a pre‑configured instance in 30 seconds, pay‑as‑you‑go
  • Effortless upgrades, fully managed without downtime
  • Automated, continuous backups with point‑in‑time recovery
  • Choose highly‑available replicated pairs for business continuity
  • Integrated metrics, logs, security and user controls at your fingertips

Lower costs

Spend less with compression savings from best‑in‑class algorithms, including delta-delta and Gorilla, and a memory‑efficient architecture.

  • Reduce storage costs with 94-97% lossless compression rates
  • Downsampling keeps aggregated metrics without wasting disk space
  • Optimize storage consumption with data retention policies
  • Transparent pricing, always know what you’ll pay
  • Dynamically scale compute and storage based on changing needs
Appdynamics

TimescaleDB was the clear answer for AppDynamics' unified monitoring platform, providing an impressive 12x cost/performance improvement over our previous database architecture.

Ty Amell

CTO, AppDynamics

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

Features

Deliver orders of magnitude greater performance and data 
storage for every query, use case, and workflow.

Cloud

Time-series analytics
Hypertable abstraction layer
Automatic chunking / partitioning
Optimized time-based constraint exclusion
Join time-series and relational tables
Built-in flexible time bucketing
Advanced analytical functions
(gapfilling, LOCF, interpolation)
Real-time aggregates
Data lifecycle management
Automated continuous aggregations
Automated data reordering on disk
Automated data retention policies
Automated downsampling
Automated native data compression
Operational management
AWS
Microsoft Azure
Google Cloud Platform
Provider
Choice of 76 deployment regions
Regions
0.5 to 72 CPUs
Compute
Up to 10TB
Provisioned storage
Up to 100+ TBs
Capacity for uncompressed data
Dynamic scaling
Instant pause/resume
High availability - Instantaneous recovery
High availability - Synchronous replicas
Read replicas and database forking
Continuous backup and recovery
Role-based access control
Data encrypted at rest and in transit
Data security
VPC peering, IP whitelisting
Advanced network security
SOC2, ISO 27001, and HIPAA compliance
Compliance
Highly-rated support team available via email, portal, and call-back; Community Slack
Support options
Choose Cloud option

Software

Time-series analytics
Hypertable abstraction layer
Automatic chunking / partitioning
Optimized time-based constraint exclusion
Join time-series and relational tables
Built-in flexible time bucketing
Advanced analytical functions
(gapfilling, LOCF, interpolation)
Real-time aggregates
Data lifecycle management
Automated continuous aggregations
Automated data reordering on disk
Automated data retention policies
Automated downsampling
Automated native data compression
Operational management
Your infrastructure
Provider
Your infrastructure
Regions
Your infrastructure
Compute
Your infrastructure
Provisioned storage
Your infrastructure
Capacity for uncompressed data
Dynamic scaling
Instant pause/resume
High availability - Instantaneous recovery
Manual
High availability - Synchronous replicas
Manual
Read replicas and database forking
Manual
Continuous backup and recovery
Manual
Role-based access control
Manual
Data security
Advanced network security
Compliance
Community Slack
Support options
Download Software

Features

Deliver orders of magnitude greater performance and data 
storage for every query, use case, and workflow.
Cloud
Software
Time-series analytics
Hypertable abstraction layer
Automatic chunking / partitioning
Optimized time-based constraint exclusion
Join time-series and relational tables
Built-in flexible time bucketing
Advanced analytical functions
(gapfilling, LOCF, interpolation)
Real-time aggregates
Data lifecycle management
Automated continuous aggregations
Automated data reordering on disk
Automated data retention policies
Automated downsampling
Automated native data compression
Operational management
Provider
AWS
Microsoft Azure
Google Cloud Platform
Your infrastructure
Regions
Choice of 76 deployment regions
Your infrastructure
Compute
0.5 to 72 CPUs
Your infrastructure
Provisioned storage
Up to 10TB
Your infrastructure
Capacity for uncompressed data
Up to 100+ TBs
Your infrastructure
Dynamic scaling
Instant pause/resume
High availability - Instantaneous recovery
High availability - Synchronous replicas
Manual
Read replicas and database forking
Manual
Continuous backup and recovery
Manual
Role-based access control
Manual
Data security
Data encrypted at rest and in transit
Manual
Advanced network security
VPC peering, IP whitelisting
Compliance
SOC2, ISO 27001, and HIPAA compliance
Support options
Highly-rated support team available via email, portal, and call-back; Community Slack
Community Slack
Getting started
1
Sign up for Cloud
Cloud is the easiest and fastest way to get started with time-series data.
Choose Cloud option
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