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TimescaleDB

PostgreSQL extension for real-time time-series analytics with hypertables, columnstore, and continuous aggregates

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Languages
  • C
  • PLpgSQL
  • Python
TimescaleDB screenshot

About TimescaleDB

TimescaleDB is a PostgreSQL extension for high-performance real-time analytics on time-series and event data. It keeps data in PostgreSQL while adding time-series storage and query features for workloads like IoT, financial analysis, and application events.

It automatically partitions data into time-based chunks, supports hypertables, and can write directly to columnstore. It also adds continuous aggregates for incremental refreshes and time_bucket() for time-series aggregation, so queries can scan only the relevant time ranges and columns.

TimescaleDB is built and maintained by TigerData (formerly Timescale) and runs as a self-hosted PostgreSQL extension. A managed option, Tiger Cloud, is also available, while the open source extension can run locally with Docker or be installed on Linux and Mac for development and testing.

Key features

  • Hypertables for time-based partitioning
  • Columnstore writes with vectorized queries
  • Continuous aggregates with incremental refresh
  • time_bucket() for time-series aggregation
  • Works as a PostgreSQL extension

Details

First released
2017
Platforms
Linux · macOS · Docker
Deployment
self-hostable · docker · cloud
Storage
PostgreSQL with columnstore
License
Apache 2.0
Maintainer
TigerData (Timescale)