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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 Овчинников
    Александр Овчинников ФКУ "Налог-Сервис"

    Diagnostic Methods: Analyzing the Issue of Long CREATE DATABASE Execution

    This talk covers two cases of long CREATE DATABASE execution in PostgreSQL 11, which, in a Corosync/Pacemaker cluster configuration, caused node failover due to a monitoring timeout from the clustering software. The first case is related to a large shared buffers size, while the second involves the use of the WITH OWNER option during database creation and a large pg_shdepend system table (a feature of using the jBPM software).

  • 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.

  • Karel van der Walt
    Karel van der Walt MentalArrow

    Experience Report addressing the manual migration of MS SQL Server Stored Procedures and Table-Valued Functions to PL/pgSQL. We chose a manual migration from T-SQL over using a PostgreSQL Extension with an automated translation. The motivation was that the T-SQL code contains non-trivial business logic for which we wanted idiomatic PL/pgSQL code. 

    The T-SQL Code used features like 

    • Mix of Stored Procedures and Table-valued Functions

    • Table variables, (user-defined) table types 

    • Recursive Common Table Expressions 

    • Optional parameters 

    The migration required

    • Adopting naming conventions 

    • Renaming parameters and local variables 

    • Maping table types 

    • Mapping table-valued parameters to arrays 

    • Mapping table-valued return types to SETOF record

    • Translating between arrays and tables 

    In this session we will migrate a chain of dependend functions T-SQL functions to PL/pgSQL. We will work around quirks in both T-SQL functions and PL/pgSQL.

  • Борис Бондарев
    Борис Бондарев

    The focus of the presentation is on the challenges of building an application solution on PostgreSQL, specifically a high-load analytical data warehouse. Using the case of the company EVRAZ, we will demonstrate the impact of applying the Data Vault methodology on PostgreSQL and Greenplum databases for developing a unified production performance system.

    We will discuss the difficulties and solutions, showcasing query plans for tasks such as updating directories and handling large objects, along with optimization examples. We will highlight coding nuances, problems related to populating the model, and issues with querying from the model.

    This session will be useful for those planning to use or already facing challenges with the Data Vault methodology and performance issues in DWH on the open-source stack. We will compare technical implementation options for the Business Vault model layer, considering the specifics of PostgreSQL and Greenplum.

    We will also cover 5 real problems that arise when operating a DWH and their solutions:

    1. Transferring Business Vault object assembly logic from PostgreSQL to Greenplum.
    2. Slower ETL performance when building the current state of Business Vault in PostgreSQL.
    3. Slower Data Lineage construction in PostgreSQL and Greenplum.
    4. Slow satellite queries in Greenplum.
    5. Slow queries with "IN" or "OR" in the Business Vault layer.

All talks

Informational