PGConf.Russia 2025

Many developers often face performance issues in the systems they develop. One common solution for optimizing slow business processes is parallelization. But what do you do if the bottleneck is the data insertion into the database, which needs to maintain atomicity?

In this talk, I’ll explain how to speed up data insertion by parallelizing the process in Spring, while ensuring the atomicity of the entire operation. We'll cover batch updates in Spring and PostgreSQL, discuss why updates are heavy operations, and explore ways to speed up the process in the current tech stack. Additionally, I will present other approaches to maintaining atomicity and demonstrate their differences in benchmarks.

This will be useful for practicing engineers.

Diagnostic Methods: Analyzing the Issue of Long CREATE DATABASE Execution

This talk covers two cases of long CREATE DATABASE execution in PostgreSQL 11, which, in a Corosync/Pacemaker cluster configuration, caused node failover due to a monitoring timeout from the clustering software. The first case is related to a large shared buffers size, while the second involves the use of the WITH OWNER option during database creation and a large pg_shdepend system table (a feature of using the jBPM software).

Covering all the key changes in PostgreSQL 18 during this talk would be quite a challenge — especially since the code freeze is set to happen just a week after the presentation. However, I’ll focus on what has already been finalized.

There are plenty of exciting updates in performance, monitoring, vacuuming (of course!), and beyond. As always, this talk is based on a series of articles reviewing the commit fests for PostgreSQL 18, published on Postgres Professional’s corporate blog on Habr.

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.