PGConf.Russia 2025

The execution time of SQL queries depends on factors like indexes and up-to-date statistics. In most cases, optimizing slow queries helps resolve database performance issues.

But what if classic query optimization doesn’t work? What if the system keeps behaving unpredictably — or worse, crashes, leading to frustration, panic, and even despair?

In this talk, we’ll explore how Postgres Professional’s performance engineers tackle these challenges, look at the tools they use, what’s still missing, and where PostgreSQL performance optimization is headed

Poolers play a crucial role in PostgreSQL database operations. In this talk, we’ll discuss the challenges we faced when using and implementing existing poolers and the benefits we gained by developing our own pooler.

In PostgreSQL performance testing, benchmarks measure query execution time (latency). To get more reliable results, queries are executed repeatedly, generating a dataset of latency values. Performance is often assessed using standard metrics like the median or mean, but we propose a more advanced approach.

In practice, latency distributions are often multimodal, consisting of multiple underlying distributions with distinct characteristics. In such cases, traditional statistical methods are insufficient, requiring a more detailed analysis of the dataset’s structure.

Our work presents a tool that automatically performs statistical analysis of benchmark results, accounting for dataset-specific features. It detects multimodality, identifies the number and boundaries of dominant modes, and determines key distribution parameters—providing deeper insights into PostgreSQL performance variations.

For over a year, Postgres Pro has provided extended vacuum statistics, reflecting its operation on individual relations.

We've started receiving observations from production databases of clients that include these statistics. It has been quite successful, and in 2024, we began actively promoting vacuum statistics in PostgreSQL. In this talk, we will review what these statistics can tell us about the complex life of vacuum, using real-world data from live systems.