PGConf.Russia 2025

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.

As part of the import substitution process, we encountered the need to find a reliable alternative to Oracle. PostgreSQL was considered the primary candidate for replacement, but during the research, the "vanilla" version revealed a number of critical limitations that hindered a successful transition.

These issues included support for autonomous transactions, batch variables, and several other specifics. What is special about pg_settings? Why do we need autonomous transactions, and how do HOLD cursors relate to this? These and other topics will be discussed in our presentation, where we will also share our experience of implementing Postgres Pro Enterprise.

In any business-critical system, there comes a need to modify table structures — whether it's adding new columns with expressions based on other columns or converting a non-partitioned table into a partitioned one.

Using standard PostgreSQL tools for large table reorganization often results in significant downtime, as tables become unavailable for writes — and sometimes even for reads — during the process.

In this talk, I’ll introduce dbms_redefinition, a custom-built extension that brings functionality similar to Oracle’s DBMS_REDEFINITION package to PostgreSQL. This solution minimizes downtime to near zero when applying schema changes in production. 

Unlike pg_repack, which does not support structural modifications, dbms_redefinition is useful for all PostgreSQL users, even beyond Oracle migrations.

I’ll share a real-world use case, discuss future development plans, and explore new features in the pipeline.

In this talk, we’ll:

• Share our experience of reworking the ECM system and platform that was originally built on C.Net + MS SQL for Windows to run on Linux + Postgres, while maintaining the option to install and operate on Windows + MS.

• Discuss migrating clients to new platforms with data migration.

• Share insights from operating the system with a high-load client (PG servers with 192 cores and 3 TB of RAM).