PostgreSQL, the Time-Series Database You Want

Time-series data is relentless, so you know you’ll have to create one or more partitioned tables (a.k.a. Timescale hypertables) to store it. Learn how to choose the best data modeling option for your use case—single or multiple hypertables.
In this recap of January’s Commitfest, our PostgreSQL developer Chris Travers shares his thoughts on improvements to psql, software development with infinite values, transaction ID wraparound problems, and more.
Visit our comprehensive docs with API reference, user guides, tutorials, and much more.
One way to optimize your data processing is by improving data locality when downsampling your data. Watch this talk at RubyConfTH, where we benchmark downsampling data in Ruby against a SQL version powered by Timescale’s hyperfunctions.
Read how Ndustrial is helping its clients save energy and money by collecting and connecting production and energy data to quickly answer real-time queries—all while using TimescaleDB to store and compress data up to 97 percent.
Learn why data locality can be crucial to downsampling data faster and more efficiently, accelerating the work of both devs and businesses. To test this new approach, we benchmarked the LTTB downsampling algorithm in Ruby and compared it with the Timescale Toolkit lttb ().
Read how Everactive consolidated its storage solution and benefited from more predictable pricing by moving its metadata from Amazon RDS to Timescale Cloud—all while expanding its cloud analytics platform powered by battery-free sensors to developers building their own solutions and services.
Read how Octave migrated from AWS Timestream to Timescale Cloud in search of a more scalable database and is revolutionizing the second-life battery market by collecting, analyzing, and storing large volumes of time-series data.
A continuous aggregate is similar to a PostgreSQL materialized view, speeding up queries. But rolling up (or downsampling) previously rolled up data can increase calculation speed while decreasing storage needs. Say hi to continuous aggregates on continuous aggregates, courtesy of TimescaleDB 2.9.