PGConf.SPB 2023

In modern data analysis, machine learning models are used as often as databases. Such IT giants as Google and Amazon have already combined them. Microsoft and Yandex are not far behind. Isn't it time to implement a machine learning model in PostgreSQL? In the report you will hear about the basics of machine learning, its implementation in databases and an example of realization as postres extension.

Hardening is the process of strengthening the security of a system in order to reduce risks from possible threats. In my presentation, I will tell you how to protect service cluster communications using TLS connections, in order to avoid accidental or unauthorized access to Patroni's REST API and ETCD storage.

As you probably know, PostgreSQL has a number of distinct features compared to other DBMSs. For example, Postgres can process and store many different types of data. However, you need to know something about them before using them. In this talk, we will find the reason why queries to the table begin to slow down (and autovacuum / vacuum has nothing to do with it) and try to speed up such queries. I will tell you how integer data types work in PostgreSQL and touch on the topic of speeding up such queries. And finally, let's talk about how to make your data in tables take up less space while increasing the speed of queries to this data.

Backup is still a stumbling block when migrating to PostgreSQL from other DBMSs. Its size directly depends on your experience and knowledge about the types of backups in PostgreSQL. In this talk, I will tell you about different types of backups, their pros and cons, and scenarios for using each type.