PGConf.Russia 2025

In any business-critical system, there comes a need to modify table structures — whether it's adding new columns with expressions based on other columns or converting a non-partitioned table into a partitioned one.

Using standard PostgreSQL tools for large table reorganization often results in significant downtime, as tables become unavailable for writes — and sometimes even for reads — during the process.

In this talk, I’ll introduce dbms_redefinition, a custom-built extension that brings functionality similar to Oracle’s DBMS_REDEFINITION package to PostgreSQL. This solution minimizes downtime to near zero when applying schema changes in production. 

Unlike pg_repack, which does not support structural modifications, dbms_redefinition is useful for all PostgreSQL users, even beyond Oracle migrations.

I’ll share a real-world use case, discuss future development plans, and explore new features in the pipeline.

Making changes to tables under production load is always a complex task. For example, when you need to change a column type (e.g., from int to bigint or from timestamp to timestamptz), or move a table to a different tablespace without losing any changes that occur during the data migration.

What if you have hundreds of such tables? With pg-transparent-alter-table, this is no longer a problem. These tasks can be solved with a single simple command:
$ pg_tat -h 0.0.0.0 -d mydb -c "alter table mytable alter column id bigint"

Key features include:

• You can specify any number of alter table commands at once.
• You can modify partitioned tables, supporting both the old inheritance-based partitioning and new declarative partitioning, including multi-level partitioning.
• You can interrupt the process at any stage and continue later without losing progress from previous stages.
• You can change your mind at any time, stop the execution, run "pg_tat --clean," and revert to the original state.
• Custom commands for changing column order.
• PostgreSQL version support: 11-17.

After more than 5 years of existence (previously called transparent-alter-type), the project has become a reliable tool actively used in production. I would like to share my experience and discuss its capabilities.

Covering all the key changes in PostgreSQL 18 during this talk would be quite a challenge — especially since the code freeze is set to happen just a week after the presentation. However, I’ll focus on what has already been finalized.

There are plenty of exciting updates in performance, monitoring, vacuuming (of course!), and beyond. As always, this talk is based on a series of articles reviewing the commit fests for PostgreSQL 18, published on Postgres Professional’s corporate blog on Habr.

Greenmask is an open-source utility for database anonymization and synthetic data generation. A common challenge in development is creating test environments that closely resemble production. In this talk, we will explore how to use Greenmask’s features to prepare a test environment with ease. 

We will discuss its architecture, database subsets, types of transformations, the reasons for integrating with the PostgreSQL driver, and porting some pg libraries. Additionally, we will explain how our technology helps businesses solve problems faster, more efficiently, and securely.