PGConf.Russia 2025

I’ll talk about the challenges you’ll face if you decide to implement a new TableAM. What to choose: Generic XLog or Custom RMGR? Why use a Custom SMGR? How to integrate PostgreSQL allocators into third-party libraries, even if they don't officially support it? What’s missing for a columnar engine (including vectorization and late materialization), and how can we work around those limitations?

In the second part, I’ll dive into the internals of pgpro_tam — a new native table engine for OLAP that supports standard data formats, various SMGRs, and, if needed, third-party schedulers and execution engines, all while adhering to ACID principles. This is designed to achieve the fastest analytics on PostgreSQL (not just plugging in DuckDB).

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

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

Every day, thousands of engineers work tirelessly to make data more accurate, reliable, and up-to-date. But sometimes, we need to do the exact opposite—corrupt it.

Whether it’s masking or replacing sensitive information, or even generating entirely new datasets while preserving key business properties, data obfuscation is a crucial task. It’s essential for testing systems, sharing data with third parties, and more. However, given the complexity of data schemas and business logic, this is far from trivial.

In this talk, we’ll explore the challenges of working with artificial data and discuss various approaches to solving them using PostgreSQL’s built-in features and external extensions.