# timescale/timescaledb

A time-series database for high-performance real-time analytics packaged as a Postgres extension

Repository: https://github.com/timescale/timescaledb
Canonical: https://ross.abutalabs.com/products/timescaledb
Homepage: https://www.tigerdata.com/
Language: C
License: NOASSERTION
License Family: other
Topics: time-series-database, postgresql, time-series, sql, postgres, tsdb, iot, financial-analysis, analytics, timescaledb, database, tigerdata, historian
Last push: 2026-08-26T16:32:59+00:00

## Health v2 (maintenance only)
Score: 99/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 99, release rhythm 98, longevity 100
- inputs: {"age_days": 3466, "days_push": 7, "days_rel": 15, "gap_med": 13, "n_releases_24m": 42}
- flags: no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 23423, forks 1140 (observed 2026-08-28T04:11:34.868495+00:00)

## What it is
TimescaleDB is an open-source PostgreSQL extension that turns Postgres into a high-performance time-series database for real-time analytics on time-series and event data. It provides hypertables with automatic time-based partitioning, hybrid row-columnar storage with compression, continuous aggregates, tiered storage, and 200+ SQL time-series functions while remaining fully Postgres-compatible.

## Use cases
- store and query IoT sensor data at scale in Postgres
- run real-time analytics dashboards on time-series metrics
- ingest high-volume event or monitoring data with fast writes
- compress historical time-series data to cut storage costs
- build continuous aggregates for pre-computed rollups
- analyze financial tick data with SQL time-series functions
- tier old data to cheap object storage automatically
- add time-series capabilities to an existing PostgreSQL application

## When to choose
- you already use PostgreSQL and want time-series scale without migrating to a new database
- you need fast ingestion plus analytical queries on live and historical data in one system
- you want SQL-native time-series features like time buckets, gap filling, and continuous aggregates
- you need hybrid row-columnar storage with high compression ratios
- you want to keep relational data (assets, customers) alongside time-series readings in one database

## When to avoid
- you need a fully managed database and don't want to self-host or use the vendor's cloud
- your workload is purely relational OLTP with no time-series component
- you require a non-Postgres ecosystem or NoSQL-style schema flexibility
- you need strict open-source licensing - the project's license is not a standard OSI-approved license
- you need multi-node horizontal scaling, which is no longer part of the open-source offering

## Facets
- artifact type: plugin
- maturity: active
- function: database, analytics, search-engine, caching, compression, monitoring
- domain: databases, analytics, time-series, iot, big-data, self-hosted
- platform: windows, self-hosted, cloud
- tags: postgresql-extension, time-series-database, hypertables, columnar-storage, real-time-analytics, continuous-aggregates, data-tiering, sql, linux, macos, docker, kubernetes

## Member repositories
- timescale/timescaledb (main) score 99

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:11:34.868495+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-29T16:56:28.830065+00:00, confidence not recorded.
  - readme: https://github.com/timescale/timescaledb (fetched 2026-08-28T04:11:34.868495+00:00, sha d3d8df08a30f)
  - homepage: https://www.tigerdata.com/ (fetched 2026-08-29T07:54:28.866604+00:00, sha f4a7e77a3ba7)
  - site_page: https://www.tigerdata.com/docs (fetched 2026-08-29T07:54:28.875927+00:00, sha 2c77f990ec60)
  - site_page: https://www.tigerdata.com/docs/about/latest/changelog (fetched 2026-08-29T07:54:28.881087+00:00, sha 3c242306717a)
  - site_page: https://www.tigerdata.com/docs/integrations/latest (fetched 2026-08-29T07:54:28.885131+00:00, sha e419a95160aa)
  - site_page: https://www.tigerdata.com/about (fetched 2026-08-29T07:54:28.886920+00:00, sha 3bbac686df04)
  - site_page: https://www.tigerdata.com/docs/use-timescale/latest/hypertables (fetched 2026-08-29T07:54:28.888576+00:00, sha 90c8ee2556f6)
  - site_page: https://www.tigerdata.com/docs/use-timescale/latest/hypercore (fetched 2026-08-29T07:54:28.890316+00:00, sha 3dad697f6e3e)
  - site_page: https://www.tigerdata.com/docs/use-timescale/latest/data-tiering/about-data-tiering (fetched 2026-08-29T07:54:28.892008+00:00, sha c864dbe77689)
  - site_page: https://www.tigerdata.com/pricing (fetched 2026-08-29T07:54:28.878658+00:00, sha a3e1d61ea5ad)
- Data as of 2026-08-30T08:39:29.467469+00:00.