Timescale

PostgreSQL-native time-series database for metrics, events, and analytics

4.0(39 reviews)freemiumFounded 2026

free tiermanaged optionbackups includedeu datacenterus datacenterapi accessopen source

Integrates with

Timescale extends PostgreSQL with TimescaleDB for high-performance time-series data. Managed cloud, auto-compression, continuous aggregates, and hyperfunctions. Free tier available.

Timescale extends PostgreSQL with automatic data partitioning, compression, and specialized indexing for time-series workloads. It maintains full SQL compatibility while handling millions of data points per second. Available as managed cloud service or self-hosted, with native support for continuous aggregates and real-time analytics.

Pros

Query time-series data with standard SQL—no new language to learn
Compress data by 90%+ automatically, reducing storage costs significantly
Handle high-throughput ingestion (millions of rows/second) without custom sharding
Run continuous aggregates for real-time dashboards without manual refresh
Leverage PostgreSQL ecosystem—extensions, tools, and libraries work natively

Cons

Requires PostgreSQL expertise; not a zero-ops managed service like some competitors
Self-hosted deployments need operational overhead for scaling and maintenance
Pricing for managed cloud can escalate with data volume and query complexity

Best For

Teams building observability platforms, infrastructure monitoring, or financial analytics who already use or prefer PostgreSQL and need native time-series performance.