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.

This talk will explore different approaches to storing files in PostgreSQL, including:

• Simple table-based storage

• Large objects with pg_largeobject

• pgpro_sfile – a large object (pgpro_bfile) storage solution

What does a modern application developer need to transition from familiar cloud-based solutions to SQL databases?

This talk is a practical report on how we transformed an SQL database into a NoSQL-like solution with a developer-friendly interface. We’ll discuss:

What application developers expect from a data framework

How to implement declarative DDL, access control, and automation for reading and writing data

Simplified DML operations, pagination, and other essential features for application development

Every day, thousands of engineers work tirelessly to make data more accurate, reliable, and up-to-date. But sometimes, we need to do the exact opposite—corrupt it.

Whether it’s masking or replacing sensitive information, or even generating entirely new datasets while preserving key business properties, data obfuscation is a crucial task. It’s essential for testing systems, sharing data with third parties, and more. However, given the complexity of data schemas and business logic, this is far from trivial.

In this talk, we’ll explore the challenges of working with artificial data and discuss various approaches to solving them using PostgreSQL’s built-in features and external extensions.