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TimescaleDB

TimescaleDB is an open-source database designed to make SQL scalable for time-series data. It is engineered up from PostgreSQL, providing automatic partitioning across time and space (partitioning key), as well as full SQL support.

TimescaleDB is packaged as a PostgreSQL extension. All code is licensed under the Apache-2 open-source license, with the exception of source code under the \tsl subdirectory, which is licensed under the Timescale License (TSL). For clarity, all code files reference licensing in their header. Contributors welcome.

Apache-2 licensed binaries can be built by passing -DAPACHE_ONLY=1 to bootstrap.

Below is an introduction to TimescaleDB. For more information, please check out these other resources:

• Developer Documentation
• Slack Channel
• Support Email

(Before building from source, see instructions below.)

Using TimescaleDB

TimescaleDB scales PostgreSQL for time-series data via automatic partitioning across time and space (partitioning key), yet retains the standard PostgreSQL interface.

In other words, TimescaleDB exposes what look like regular tables, but are actually only an abstraction (or a virtual view) of many individual tables comprising the actual data. This single-table view, which we call a hypertable, is comprised of many chunks, which are created by partitioning the hypertable's data in either one or two dimensions: by a time interval, and by an (optional) "partition key" such as device id, location, user id, etc. (Architecture discussion)

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.

From the perspective of both use and management, TimescaleDB just looks and feels like PostgreSQL, and can be managed and queried as such.

Before you start

PostgreSQL's out-of-the-box settings are typically too conservative for modern servers and TimescaleDB. You should make sure your postgresql.conf settings are tuned, either by using timescaledb-tune or doing it manually.

Creating a hypertable

-- Do not forget to create timescaledb extension
CREATE EXTENSION timescaledb;

-- We start by creating a regular SQL table
CREATE TABLE conditions (
  time        TIMESTAMPTZ       NOT NULL,
  location    TEXT              NOT NULL,
  temperature DOUBLE PRECISION  NULL,
  humidity    DOUBLE PRECISION  NULL
);

-- Then we convert it into a hypertable that is partitioned by time
SELECT create_hypertable('conditions', 'time');

• Quick start: Creating hypertables
• Reference examples

Inserting and querying data

Inserting data into the hypertable is done via normal SQL commands:

INSERT INTO conditions(time, location, temperature, humidity)
  VALUES (NOW(), 'office', 70.0, 50.0);

SELECT * FROM conditions ORDER BY time DESC LIMIT 100;

SELECT time_bucket('15 minutes', time) AS fifteen_min,
    location, COUNT(*),
    MAX(temperature) AS max_temp,
    MAX(humidity) AS max_hum
  FROM conditions
  WHERE time > NOW() - interval '3 hours'
  GROUP BY fifteen_min, location
  ORDER BY fifteen_min DESC, max_temp DESC;

In addition, TimescaleDB includes additional functions for time-series analysis that are not present in vanilla PostgreSQL. (For example, the time_bucket function above.)

• Quick start: Basic operations
• Reference examples
• TimescaleDB API

Installation

TimescaleDB is available pre-packaged for several platforms:

• Linux:
  • RedHat / CentOS
  • Ubuntu
  • Debian
• Docker
• MacOS (Homebrew)
• Windows

We recommend following our detailed installation instructions.

Building from source (Unix-based systems)

If you are building from source for non-development purposes (i.e., you want to run TimescaleDB, not submit a patch), you should always use a release-tagged commit and not build from master. See the Releases tab for the latest release.

Prerequisites:

• A standard PostgreSQL 9.6 or 10 installation with development environment (header files) (e.g., postgresql-server-dev-9.6 package for Linux, Postgres.app for MacOS)
• C compiler (e.g., gcc or clang)
• CMake version 3.4 or greater

git clone [email protected]:timescale/timescaledb.git
cd timescaledb
# Find the latest release and checkout, e.g. for 1.0.0:
git checkout 1.0.0
# Bootstrap the build system
./bootstrap
# To build the extension
cd build && make
# To install
make install

Note, if you have multiple versions of PostgreSQL installed you can specify the path to pg_config that should be used by using ./bootstrap -DPG_CONFIG=/path/to/pg_config.

Please see our additional configuration instructions.

Building from source (Windows)

If you are building from source for non-development purposes (i.e., you want to run TimescaleDB, not submit a patch), you should always use a release-tagged commit and not build from master. See the Releases tab for the latest release.

Prerequisites:

• A standard PostgreSQL 9.6 or 10 64-bit installation
• OpenSSL for Windows
• Microsoft Visual Studio 2017 with CMake and Git components
• OR Visual Studio 2015/2016 with CMake version 3.4 or greater and Git
• Make sure all relevant binaries are in your PATH: pg_config and cmake

If using Visual Studio 2017 with the CMake and Git components, you should be able to simply clone the repo and open the folder in Visual Studio which will take care of the rest.

If you are using an earlier version of Visual Studio, then it can be built in the following way:

git clone [email protected]:timescale/timescaledb.git
cd timescaledb

# Find the latest release and checkout, e.g. for 1.0.0:
git checkout 1.0.0
# Bootstrap the build system
bootstrap.bat
# To build the extension from command line
cmake --build ./build --config Release
# To install
cmake --build ./build --config Release --target install

# Alternatively, build in Visual Studio via its built-in support for
# CMake or by opening the generated build/timescaledb.sln solution file.

Useful tools

• timescaledb-tune: Helps set your PostgreSQL configuration settings based on your system's resources.
• timescaledb-parallel-copy: Parallelize your initial bulk loading by using PostgreSQL's COPY across multiple workers.

Additional documentation

• Why use TimescaleDB?
• Migrating from PostgreSQL
• Writing data
• Querying and data analytics
• Tutorials and sample data

Support

• Slack Channel
• Github Issues
• Support Email

Contributing

• Contributor instructions
• Code style guide