PGConf.Russia 2025

The focus of the presentation is on the challenges of building an application solution on PostgreSQL, specifically a high-load analytical data warehouse. Using the case of the company EVRAZ, we will demonstrate the impact of applying the Data Vault methodology on PostgreSQL and Greenplum databases for developing a unified production performance system.

We will discuss the difficulties and solutions, showcasing query plans for tasks such as updating directories and handling large objects, along with optimization examples. We will highlight coding nuances, problems related to populating the model, and issues with querying from the model.

This session will be useful for those planning to use or already facing challenges with the Data Vault methodology and performance issues in DWH on the open-source stack. We will compare technical implementation options for the Business Vault model layer, considering the specifics of PostgreSQL and Greenplum.

We will also cover 5 real problems that arise when operating a DWH and their solutions:

1. Transferring Business Vault object assembly logic from PostgreSQL to Greenplum.
2. Slower ETL performance when building the current state of Business Vault in PostgreSQL.
3. Slower Data Lineage construction in PostgreSQL and Greenplum.
4. Slow satellite queries in Greenplum.
5. Slow queries with "IN" or "OR" in the Business Vault layer.

The issue of slow month-end closing and cost calculation on PostgreSQL has been a long-standing problem. In this talk, we will explore what modern versions of PostgreSQL offer in this regard and answer the question, "Do replicas slow down the master?"

We will also take a look at different types of physical replication and, for dessert, share a recipe for quick and painless month-end closing in 1C without affecting the daily operations of users.

For over a year, Postgres Pro has provided extended vacuum statistics, reflecting its operation on individual relations.

We've started receiving observations from production databases of clients that include these statistics. It has been quite successful, and in 2024, we began actively promoting vacuum statistics in PostgreSQL. In this talk, we will review what these statistics can tell us about the complex life of vacuum, using real-world data from live systems.

Last year, we introduced built-in fault tolerance support in Postgres Pro Enterprise through BiHA. Our solution allows you to deploy a fault-tolerant Postgres cluster where, in the event of a failure of the primary node, a new primary node (leader) is automatically selected.

However, this brings up the issue of redirecting traffic to the new leader. This can be solved using our Proxima extension or an external TCP proxy server. Both solutions needed to periodically query the BiHA cluster to determine the primary node.

As an alternative, the latest version of BiHA introduced the ability to register custom functions that will be triggered by events such as leader change, node addition/removal, and others. We call this mechanism user callbacks. In this presentation, we’ll explain how the callbacks are implemented and discuss their usage.