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

Last year, we introduced built-in fault tolerance support in Postgres Pro Enterprise through BiHA. Our solution allows you to deploy a fault-tolerant Postgres cluster where, in the event of a failure of the primary node, a new primary node (leader) is automatically selected.

However, this brings up the issue of redirecting traffic to the new leader. This can be solved using our Proxima extension or an external TCP proxy server. Both solutions needed to periodically query the BiHA cluster to determine the primary node.

As an alternative, the latest version of BiHA introduced the ability to register custom functions that will be triggered by events such as leader change, node addition/removal, and others. We call this mechanism user callbacks. In this presentation, we’ll explain how the callbacks are implemented and discuss their usage.

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).

What does a modern application developer need to transition from familiar cloud-based solutions to SQL databases?

This talk is a practical report on how we transformed an SQL database into a NoSQL-like solution with a developer-friendly interface. We’ll discuss:

What application developers expect from a data framework

How to implement declarative DDL, access control, and automation for reading and writing data

Simplified DML operations, pagination, and other essential features for application development