PGConf.Russia 2025

Databases are a core component of any information system, and query performance directly impacts overall efficiency.

Last year, we explored suboptimal queries and optimization techniques, and the topic proved highly relevant. In this second installment, we’ll cover:

Using extended statistics for computed columns

Pagination techniques for improved query handling

Real-world optimization examples from 1C

Where I used to work, we had pushed ElasticSearch to its breaking point. We needed an even more scalable replacement for a write-heavy, read-seldom workload. So we built one on PostgreSQL. Now, many of us are building the successor as an open source project. 

This talk goes over the design of Bagger (named after the giant mining machines), which can manage logs into tens or hundreds of petabytes. More than just a review of the architecture, this talk focuses on the whys and the tradeoffs made in the design. 

The talk is intended both to showcase how programmable and powerful PostgreSQL is, but also illustrate the fundamental tradeoffs which must be faced when pushing any technology into the big data space.

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.

In today’s rapidly evolving technology landscape, PostgreSQL has emerged as a popular choice for organizations seeking to leverage the power of open-source databases while maintaining scalability, performance, and flexibility. 

As enterprises migrate from proprietary database systems like Oracle to PostgreSQL, developers face the challenge of adapting existing PL/SQL codebases to PL/pgSQL. Despite the similarities between these two procedural languages, significant differences in their syntax, performance characteristics, and ecosystem features require a thoughtful approach to migration and optimization. 

This session will focus on highlighting the key differences between Oracle’s PL/SQL and PostgreSQL’s PL/pgSQL, providing actionable insights on how to efficiently navigate these differences during migration. A deep dive will be taken into critical areas including compilation methodology, Code Debugging , Exception Handling, work_mem , Bulk Load and more.