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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
  • Александр Попов
    Александр Попов PostgresPro

    This talk will explore different approaches to storing files in PostgreSQL, including:

    • Simple table-based storage

    • Large objects with pg_largeobject

    • pgpro_sfile – a large object (pgpro_bfile) storage solution

  • Евгений Бредня
    Евгений Бредня PostgresPro

    In 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.

  • Anton Doroshkevich
    Anton Doroshkevich Инфософт

    The issue of slow month-end closing and cost calculation on PostgreSQL has been a long-standing problem. In this talk, we will explore what modern versions of PostgreSQL offer in this regard and answer the question, "Do replicas slow down the master?"

    We will also take a look at different types of physical replication and, for dessert, share a recipe for quick and painless month-end closing in 1C without affecting the daily operations of users.

  • 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.

All talks

Informational