PGConf.Russia 2022

The volume of data stored in Postgres Pro databases is growing rapidly. In some organizations, such databases have already exceeded tens of terabytes in size. The existing approaches to backups don't ensure timely backup and restore of data in such cases. We have supplemented the well-known and well-tested Postgres Pro backup tools with functionality that will allow users to backup and restore large databases. In addition to that, we have created our solution with the convenience of DBAs in mind.

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.

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.