31 March – 01 April 2025
PGConf.Russia 2025
PGConf.Russia is the largest PostgreSQL conference in Russia and the CIS. The event offers technical sessions, hands-on demos of new DBMS features, master classes, networking opportunities, and knowledge exchange with top PostgreSQL community experts. Each year, hundreds of professionals participate, including DBAs, database architects, developers, QA engineers, and IT managers.
Agenda highlights
-
Latest news and updates from the PostgreSQL global community
-
Monitoring, high availability, and security
-
Streamlined migration from Oracle, Microsoft SQL Server, and other systems
-
Query optimization
-
Scalability, sharding and partitioning
-
AI applications in DBMS
-
PostgreSQL compatibility with other software
Talks
Talks archive
-
Евгений Бредня PostgresProIn this talk, we will discuss what character encodings and collations are. I will explain the issues that can arise from sorting (COLLATION) in databases and show how these problems can be addressed using the COLLATION PROVIDER = ICU feature in PostgreSQL.
-
Pavel Luzanov PostgresProCovering all the key changes in PostgreSQL 18 during this talk would be quite a challenge — especially since the code freeze is set to happen just a week after the presentation. However, I’ll focus on what has already been finalized.
There are plenty of exciting updates in performance, monitoring, vacuuming (of course!), and beyond. As always, this talk is based on a series of articles reviewing the commit fests for PostgreSQL 18, published on Postgres Professional’s corporate blog on Habr.
-
Dmitry Vasilyev OZONPoolers 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.
-
Евгений Бузюркин PostgresPro
Дарья Барсукова НГУ
Рустам Хамидуллин PostgresProIn 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.
Photos
Photo archive