PGConf.Russia 2025

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.

Not a PgBouncer, But a Connection Pooler. Not Odyssey, But with Coroutines

If you’ve ever set up a high-availability PostgreSQL cluster, you’ve likely faced the challenge of redirecting traffic to the primary node after a failover.

Typically, this requires additional software to monitor cluster status and reroute traffic accordingly. To avoid a single point of failure, you may have had to implement failover handling within that layer. Additionally, you might have encountered PostgreSQL’s limitations on handling large numbers of concurrent client sessions, necessitating query pooling.

To solve these issues, we developed Proxima — a scalable, fault-tolerant proxy and connection pooler. Proxima automatically redirects traffic to the primary node and, in BiHA setups, seamlessly switches to a new primary in case of failure.

In this talk, I’ll cover why and how we built Proxima, the key architectural decisions behind the extension, and the

implementation details that enable it to handle 10,000+ concurrent client sessions.

We’ll also explore use cases and answer your questions.

Every day, thousands of engineers work tirelessly to make data more accurate, reliable, and up-to-date. But sometimes, we need to do the exact opposite—corrupt it.

Whether it’s masking or replacing sensitive information, or even generating entirely new datasets while preserving key business properties, data obfuscation is a crucial task. It’s essential for testing systems, sharing data with third parties, and more. However, given the complexity of data schemas and business logic, this is far from trivial.

In this talk, we’ll explore the challenges of working with artificial data and discuss various approaches to solving them using PostgreSQL’s built-in features and external extensions.

Greenmask is an open-source utility for database anonymization and synthetic data generation. A common challenge in development is creating test environments that closely resemble production. In this talk, we will explore how to use Greenmask’s features to prepare a test environment with ease. 

We will discuss its architecture, database subsets, types of transformations, the reasons for integrating with the PostgreSQL driver, and porting some pg libraries. Additionally, we will explain how our technology helps businesses solve problems faster, more efficiently, and securely.