PGConf.Russia 2025

This presentation examines the challenges of migrating an application system from Oracle to Postgres, based on a real-world project. It provides a detailed discussion on logical replication of data from Postgres to ensure the possibility of reverting back to Oracle while maintaining the functionality of legacy reporting and integration.

The visibility map in PostgreSQL is an important mechanism for optimizing database performance, accelerating read operations, data cleanup, and indexing. Despite some limitations, such as memory consumption and fragmentation, its use can significantly enhance performance in high-load systems. Effective utilization of the visibility map requires proper configuration and monitoring, which is especially crucial in systems with large data volumes and high transaction concurrency.

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.