PGConf.Russia 2025

Currently, WAL files can be compressed with a ratio of up to 6x, but the existing compression system is inefficient.

In this talk, I’ll share my work on improving WAL compression.

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.

The issue of slow month-end closing and cost calculation on PostgreSQL has been a long-standing problem. In this talk, we will explore what modern versions of PostgreSQL offer in this regard and answer the question, "Do replicas slow down the master?"

We will also take a look at different types of physical replication and, for dessert, share a recipe for quick and painless month-end closing in 1C without affecting the daily operations of users.