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.

In today’s rapidly evolving technology landscape, PostgreSQL has emerged as a popular choice for organizations seeking to leverage the power of open-source databases while maintaining scalability, performance, and flexibility. 

As enterprises migrate from proprietary database systems like Oracle to PostgreSQL, developers face the challenge of adapting existing PL/SQL codebases to PL/pgSQL. Despite the similarities between these two procedural languages, significant differences in their syntax, performance characteristics, and ecosystem features require a thoughtful approach to migration and optimization. 

This session will focus on highlighting the key differences between Oracle’s PL/SQL and PostgreSQL’s PL/pgSQL, providing actionable insights on how to efficiently navigate these differences during migration. A deep dive will be taken into critical areas including compilation methodology, Code Debugging , Exception Handling, work_mem , Bulk Load and more.

Where I used to work, we had pushed ElasticSearch to its breaking point. We needed an even more scalable replacement for a write-heavy, read-seldom workload. So we built one on PostgreSQL. Now, many of us are building the successor as an open source project. 

This talk goes over the design of Bagger (named after the giant mining machines), which can manage logs into tens or hundreds of petabytes. More than just a review of the architecture, this talk focuses on the whys and the tradeoffs made in the design. 

The talk is intended both to showcase how programmable and powerful PostgreSQL is, but also illustrate the fundamental tradeoffs which must be faced when pushing any technology into the big data space.

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.