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My main advice when running performance benchmarks for Postgres is: “Automate it!”
If you’re measuring database performance, you are likely going to have to run the same benchmark over and over again. Either because you want a slightly different configuration, or because you realized you used some wrong settings, or maybe some other reason. By automating the way you’re running performance benchmarks, you won’t be too annoyed when this happens, because re-running the benchmarks will cost very little effort (it will only cost some time).
However, building this automation for the database benchmarks can be very time-consuming, too. So, in this post I’ll share the tools I built to make it easy to run benchmarks against Postgres—specifically against the Citus extension to Postgres running in a managed database service on Azure called Hyperscale (Citus) in Azure Database for PostgreSQL.
Here’s your map for reading this post: each anchor link takes you to a different section. The first sections explore the different types of application workloads and their characteristics, plus the off-the-shelf benchmarks that are commonly used for each. After that you can dive into the “how to” aspects of using HammerDB with Citus and Postgres on Azure. And yes, you’ll see some sample benchmarking results, too.Keep reading