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.

Databases are a core component of any information system, and query performance directly impacts overall efficiency.

Last year, we explored suboptimal queries and optimization techniques, and the topic proved highly relevant. In this second installment, we’ll cover:

Using extended statistics for computed columns

Pagination techniques for improved query handling

Real-world optimization examples from 1C

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.

For DBAs, ensuring database protection and integrity is always a top priority. Along with that comes the need to store data efficiently and compactly, without overloading the network, and ensuring reliable recovery.

In this talk, we’ll discuss a universal solution for backup and archive storage that not only offers effective deduplication but also minimizes network load. TATLIN.BACKUP is a platform for storing PostgreSQL backups or WAL archives with compression, deduplication, and minimal data transmission over the network.

TATLIN.BACKUP is a versatile solution for transferring and storing PostgreSQL archives at remote locations from a central office.