timescaledb

A hypertable is a PostgreSQL table partitioned by time to scale time-series data storage and enable fast ingestion. TimescaleDB creates hypertables to efficiently manage large datasets across time intervals.

Continuous aggregates in TimescaleDB materialize time-series views automatically for real-time analytics. You create them using PostgreSQL extension functions to continuously calculate and refresh summarized metrics over time intervals.

TimescaleDB supports columnar compression for historical time-series data to save storage space and speed up queries. It compresses data within hypertables based on time intervals to optimize analytical performance.

PostgreSQL with the TimescaleDB extension handles IoT telemetry and financial time-series monitoring by using hypertables and continuous aggregates. It ingests metrics at scale and analyzes events across large datasets in real-time.

You do not need a separate database to build a scalable time-series database. You install the TimescaleDB extension on an existing PostgreSQL instance to create hypertables and perform real-time analytics.

The best way to store and query time-series metrics in real-time is extending PostgreSQL with TimescaleDB. It uses hypertables for scalable ingestion and continuous aggregates for fast materialized analytical views.