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.

This talk will cover key aspects of migrating from SQL Server to PostgreSQL, with a focus on converting stored procedures, triggers, views, functions, and other database objects. We’ll discuss the unique characteristics of each database system that can complicate code conversion, as well as unexpected factors that impact performance and correctness.

The session will be valuable for both experienced database professionals and those new to database migrations.

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

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.