PGConf.Russia 2025

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.

In PostgreSQL performance testing, benchmarks measure query execution time (latency). To get more reliable results, queries are executed repeatedly, generating a dataset of latency values. Performance is often assessed using standard metrics like the median or mean, but we propose a more advanced approach.

In practice, latency distributions are often multimodal, consisting of multiple underlying distributions with distinct characteristics. In such cases, traditional statistical methods are insufficient, requiring a more detailed analysis of the dataset’s structure.

Our work presents a tool that automatically performs statistical analysis of benchmark results, accounting for dataset-specific features. It detects multimodality, identifies the number and boundaries of dominant modes, and determines key distribution parameters—providing deeper insights into PostgreSQL performance variations.

Dozens of PostgreSQL instances have replaced a single large Oracle database. One of our key business systems was completely redesigned and rebuilt on an import-independent solution.  

This talk will cover the unique challenges, architecture, issues, and operational aspects of this migration. Expect an insightful deep dive into the process!

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.