PostgreSQL extension for real-time time-series analytics with hypertables, columnstore, and continuous aggregates
Other
- C
- PLpgSQL
- Python

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)
