PGConf.Russia 2025

Two years ago, I spoke about data retrieval queries, where the LINQ to DB library offers almost limitless possibilities.

This talk is about data modification operations. LINQ to DB allows you to execute UPDATE + JOIN queries, INSERT FROM SELECT, supports the MERGE operator, row-level locking with SELECT FOR UPDATE, temporary table creation, and features a fast data insertion mechanism.

I will also discuss the linq2db. EntityFrameworkCore project — a solution for those who aren’t ready to leave EF Core but still want the capabilities of LINQ to DB. I’ll share our experience implementing LINQ to DB in a large-scale project.

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.

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.

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!