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).

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.

Poolers play a crucial role in PostgreSQL database operations. In this talk, we’ll discuss the challenges we faced when using and implementing existing poolers and the benefits we gained by developing our own pooler.

The visibility map in PostgreSQL is an important mechanism for optimizing database performance, accelerating read operations, data cleanup, and indexing. Despite some limitations, such as memory consumption and fragmentation, its use can significantly enhance performance in high-load systems. Effective utilization of the visibility map requires proper configuration and monitoring, which is especially crucial in systems with large data volumes and high transaction concurrency.