PGConf.Russia 2025

The work of a DBA is very multifaceted: backups, version updates, performance issues — there's a long list. But sometimes, due to the workload, we don't give enough attention to innovations that don't directly relate to what we do every day. Such is the case with logical replication.

Of course, each of us has some skills working with this tool, but PostgreSQL is a rapidly evolving database system. Sometimes, we simply need to look around with a fresh perspective to see something new.

My presentation will be based on this approach: we'll start with theory (as always, less theory, more practice) and simple examples, then move on to more complex examples of its use. Special attention will be given to what has changed in modern versions of PostgreSQL.

This presentation will be helpful for those who want to get acquainted with logical replication or refresh their knowledge of this tool.

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.

Databases are a core component of any information system, and query performance directly impacts overall efficiency.

Last year, we explored suboptimal queries and optimization techniques, and the topic proved highly relevant. In this second installment, we’ll cover:

Using extended statistics for computed columns

Pagination techniques for improved query handling

Real-world optimization examples from 1C