Compared to PostgreSQL alone, TimescaleDB can dramatically improve query performance by 1000x or more, reduce storage utilization by 90%, and provide features essential for time-series and analytical applications. Some of these features even benefit non-time-series data–increasing query performance just by loading the extension.
PostgreSQL is today’s most advanced and most popular open-source relational database. We believe this as much today as we did 5 years ago, when we chose PostgreSQL as the foundation of TimescaleDB because of its longevity, extensibility, and rock-solid architecture.
By loading the TimescaleDB extension into a PostgreSQL database, you can effectively “supercharge” PostgreSQL, empowering it to excel for both time-series workloads and classic transactional ones.
This article highlights how TimescaleDB improves PostgreSQL query performance at scale, increases storage efficiency (thus lowering costs), and provides developers with the tools necessary for building modern, innovative, and cost-effective time-series applications – all while retaining access to the full Postgres feature-set and ecosystem.