PGConf.Russia 2025

This talk will likely be of interest to network providers who can enhance their cool features by adding something to the syntax to simplify administration, as well as anyone interested in machine learning. We will explore the SQL parsing mechanism, what, where, and how to modify it in order to introduce new syntax constructs. Additionally, I will demonstrate the capabilities of machine learning on tabular data, all within the database, using the new syntax.

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.

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.

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