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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

  • more than
    0 participants
  • 0 speakers
  • 0
    minutes of conversation
  • 63 talks
  • hybrid
    format

Talks

Talks archive

PGConf.Russia 2025
  • Mikhail Zhilin
    Mikhail Zhilin PostgresPro

    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

  • Dmitry Vasilyev
    Dmitry Vasilyev OZON

    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.

  • Евгений Бузюркин
    Евгений Бузюркин PostgresPro
    Дарья Барсукова
    Дарья Барсукова НГУ
    Рустам Хамидуллин
    Рустам Хамидуллин PostgresPro

    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.

  • Andrey Zubkov
    Andrey Zubkov PostgresPro

    For over a year, Postgres Pro has provided extended vacuum statistics, reflecting its operation on individual relations.

    We've started receiving observations from production databases of clients that include these statistics. It has been quite successful, and in 2024, we began actively promoting vacuum statistics in PostgreSQL. In this talk, we will review what these statistics can tell us about the complex life of vacuum, using real-world data from live systems.

All talks

Informational