PGConf.Russia 2025

Many developers often face performance issues in the systems they develop. One common solution for optimizing slow business processes is parallelization. But what do you do if the bottleneck is the data insertion into the database, which needs to maintain atomicity?

In this talk, I’ll explain how to speed up data insertion by parallelizing the process in Spring, while ensuring the atomicity of the entire operation. We'll cover batch updates in Spring and PostgreSQL, discuss why updates are heavy operations, and explore ways to speed up the process in the current tech stack. Additionally, I will present other approaches to maintaining atomicity and demonstrate their differences in benchmarks.

This will be useful for practicing engineers.

This talk will cover key aspects of migrating from SQL Server to PostgreSQL, with a focus on converting stored procedures, triggers, views, functions, and other database objects. We’ll discuss the unique characteristics of each database system that can complicate code conversion, as well as unexpected factors that impact performance and correctness.

The session will be valuable for both experienced database professionals and those new to database migrations.

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 DBAs, ensuring database protection and integrity is always a top priority. Along with that comes the need to store data efficiently and compactly, without overloading the network, and ensuring reliable recovery.

In this talk, we’ll discuss a universal solution for backup and archive storage that not only offers effective deduplication but also minimizes network load. TATLIN.BACKUP is a platform for storing PostgreSQL backups or WAL archives with compression, deduplication, and minimal data transmission over the network.

TATLIN.BACKUP is a versatile solution for transferring and storing PostgreSQL archives at remote locations from a central office.