PGConf.Russia 2025

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.

Currently, WAL files can be compressed with a ratio of up to 6x, but the existing compression system is inefficient.

In this talk, I’ll share my work on improving WAL compression.

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.

In any business-critical system, there comes a need to modify table structures — whether it's adding new columns with expressions based on other columns or converting a non-partitioned table into a partitioned one.

Using standard PostgreSQL tools for large table reorganization often results in significant downtime, as tables become unavailable for writes — and sometimes even for reads — during the process.

In this talk, I’ll introduce dbms_redefinition, a custom-built extension that brings functionality similar to Oracle’s DBMS_REDEFINITION package to PostgreSQL. This solution minimizes downtime to near zero when applying schema changes in production. 

Unlike pg_repack, which does not support structural modifications, dbms_redefinition is useful for all PostgreSQL users, even beyond Oracle migrations.

I’ll share a real-world use case, discuss future development plans, and explore new features in the pipeline.