PGConf.Russia 2025

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.

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.

t’s well known that pg_upgrade is the go-to tool for fast PostgreSQL upgrades. However, even with this tool, there are cases where the upgrade process takes far longer than expected.

In our case, upgrading a PostgreSQL database with 350,000 tables meant either waiting 3.5 hours or finding a better approach. By digging into the pg_upgrade source code, we discovered a way to speed up the process significantly. In this talk, we’ll share how we did it.