PGConf.Russia 2022

A modern database should be capable of storing big values. Storing itself is not a big deal, however, operations with big values or fields are a non-trivial task. PostgreSQL has several options for storing big values, but none of them is perfect. How do we respond to this challenge? Our presentation answers this question, let's see how to store big and complex values in Postgres properly, and how operate with them.

Logical decoding and replication slots introduced in PostgreSQL 9.4 (released in 2014) created a solid foundation for implementing built-in core logical replication in version 10 (released in 2017). Unfortunately, there are a few limitations that make logical replication not very useful in real-world scenarios. Logical decoding currently isn’t supported on the standby server, and PostgreSQL allows creating logical replication slots only on the primary server. Or in other words, logical slots are lost on failover/switchover.

Postgres hackers made many attempts to address the problem, and most of them resulted in not too much success. Although, there is one little function introduced in PostgreSQL 11 that made it possible to implement failover of logical replication slots externally.

In my talk I will tell a story of how Patroni solves the problem of logical replication slots failover without using invasive third-party extensions, dig down into some of the Postgres internals in order to prove why this approach is safe, and finally, we will discuss limitations and potential downsides of this solution.

Usage of temporary tables in PostgreSQL causes additional issues like high server resources consumption and low query performance. However, sometimes you need to rely on them especially when you need to migrate your code from MS SQL, and your initial code employed them, and you had some logic implemented at the database level. This talk covers issues related to usage of temporary tables when migrating from MS SQL, and the ways to resolve them using built-in PostgreSQL features based on the scenarios contained in the code.

I am going to explain a sorting method added in Postgres 14 that allows to create GiST index much faster. We'll also talk about the disadvantages of this sorting method discovered during implementation of its support in PostGIS and how it will be improved in the future. Also, new features and improvements included in PostGIS 3.2 will be reviewed.