PGConf.Russia 2022

As opposed to in-memory DBMSs, traditional disc database management systems have an inherent physical limitation. It's their storage system which is by several orders of magnitude slower than CPU operation memory, even in the case of All-Flash NVM. It becomes especially critical for the development of business analytics apps and OLAP scenarios on disc DBMS. We will consider a number how-tos for improving the performance of traditional DBMSs, and then offer a new storage-centric approach to hardware-based speed-up for disc DBMSs.

The more tables are involved with the query, the more difficult it is for the scheduler to choose a suitable execution plan (both time and memory usage increase). How can we "tell" the planner that it is better to connect this pair of tables first, and the rest can be connected later? What if we see that a part of our query can be improved, but the optimizer does not do this. In my presentation, I will talk about managing the order of connections. I will explain how we can influence the formation of a query plan using the standard "vanilla" PostgreSQL methods.

Mamonsu is an active monitoring agent for PostgresSQL based on Zabbix. We are actively developing the agent: there are new unique metrics and visualization capabilities. But in addition to metrics collecting mechanism, Mamonsu has other useful features. I am going to briefly describe these features also known as "Mamonsu tools", the agent's advantages and the installation process.

In this presentation, we'll talk about the newest SQL/JSON features committed to PostgreSQL 15. We'll explain how to use them, where they can help and why they make a difference. Is PostgreSQL JSON implementation fully compliant with SQL:2016? In the meantime, the next generation of the SQL standard is being developed. What will the new standard include, and how will Postgres respond to it?