PGConf.SPB 2023

During the years of its existence, Postgres Pro piled up a pool of problems when query execution was inappropriately slow or a query was too expensive to be executed, so it was never executed. Almost always in our practice, this was due to the choice of a non-optimal query plan. In our story, we will talk about a very unconventional attempt to solve this problem by re-planning queries. We will tell you what it is, how it works, who will find it helpful and the prospects for using this feature.

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.

In this brief overview presentation we will discuss Postgres Pro Enterprise Manager (PPEM) capabilities, and how it helps DBAs to be more productive.

Postgres Pro Enterprise is based on open source PostgreSQL. However, the difference is significant: the current version of Postgres Pro Enterprise has 40 more features that are not a part of PostgreSQL. 20 more mechanisms are being developed either as built-in features or separate products. This includes BiHA, DBaaS, pg_probackup, etc. In this presentation, we'll briefly discuss some of them.