TimescaleDB

TimescaleDB makes Postgres fast at time-series workloads: server metrics, IoT sensor readings, financial ticks, event logs. It's not a separate database, it's an extension on top of Postgres, so your existing tools, ORMs, and SQL knowledge all still work. The key trick is hypertables, which automatically partition data by time so a query like average CPU over the last hour stays fast even across billions of rows. Continuous aggregates pre-compute rollups, and compression cuts storage by 90%+ on time-series data.

The community edition is free and open source to self-host. It installs as a Postgres extension, so if you can install extensions, you can run it. The company behind it rebranded from Timescale to TigerData, and the managed offering is now Tiger Cloud, positioned as fast Postgres generally rather than just time-series. The open-source extension is still called TimescaleDB and still ships under Apache 2.0 plus the Timescale License for the community features, so no license change, just a new name on the cloud.

Solo: self-host on your existing Postgres, free. Small teams: self-host, or use Tiger Cloud, which starts around $30/mo for the Performance tier and $36/mo for Scale, with a 30-day trial. Medium to large: weigh Tiger Cloud against self-hosting based on whether you want to own HA and backups. Self-hosting stays straightforward here since it's just an extension.

The catch: some advanced features (multi-node, certain compression options) sit under the Timescale License rather than pure Apache, so check it for your use case, especially if you're building a competing managed service. And if your workload is pure metrics with Prometheus-style queries, VictoriaMetrics or InfluxDB may be more purpose-built than general Postgres.