PGConf.Russia 2025

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.

Over the past year, pgpro_redefinition has undergone significant enhancements. In this talk, we’ll review the key updates, improvements, and new capabilities that have been introduced.

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.

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.