PGConf.Russia 2025

t’s well known that pg_upgrade is the go-to tool for fast PostgreSQL upgrades. However, even with this tool, there are cases where the upgrade process takes far longer than expected.

In our case, upgrading a PostgreSQL database with 350,000 tables meant either waiting 3.5 hours or finding a better approach. By digging into the pg_upgrade source code, we discovered a way to speed up the process significantly. In this talk, we’ll share how we did it.

Where I used to work, we had pushed ElasticSearch to its breaking point. We needed an even more scalable replacement for a write-heavy, read-seldom workload. So we built one on PostgreSQL. Now, many of us are building the successor as an open source project. 

This talk goes over the design of Bagger (named after the giant mining machines), which can manage logs into tens or hundreds of petabytes. More than just a review of the architecture, this talk focuses on the whys and the tradeoffs made in the design. 

The talk is intended both to showcase how programmable and powerful PostgreSQL is, but also illustrate the fundamental tradeoffs which must be faced when pushing any technology into the big data space.

In some cases, business logic is implemented directly within the database. It's well known that maintaining and developing business logic becomes much easier when it's covered by tests. However, backend tests often treat the database as an external resource and don’t always interact with a live database.

This talk will introduce an enhanced version of the pgTap library, designed not only to facilitate unit testing and CI for database code but also to accelerate the development process itself.

This talk addresses a common issue and touches a bit on application architecture. Temporary tables in database applications are typically used for several purposes. 

Firstly, they are used to store intermediate results when implementing complex data processing algorithms. Secondly, in the case of stored procedures, application servers often place large datasets into temporary tables when they are too large or inconvenient to pass as parameters to stored procedures. 

The handling of temporary tables in different DBMSs is implemented in various ways, which often complicates migration from these systems to Postgres. 

The drawbacks of temporary tables are well-known, which leads to a reasonable desire to replace them, where possible, with other methods that can achieve the same goal. This talk focuses on alternative mechanisms provided by Postgres to solve this problem.