PGConf.Russia 2022

Tasks for migrations from the classic commercial DBMSs to open-source solutions are still relevant nowadays. Tools used to migrate Oracle applications to PostgreSQL has already proved to be efficient. But what if you have SQL Server? We want to introduce you to Babelfish, a OSS solution based on PostgreSQL 13. Babelfish supports TDS network protocol, T-SQL language, and SQL extensions specific to SQL Server. However, it isn't that simple. In our talk, we'll cover the features ensuring compatibility with SQL Server, existing problems and ways to solve them. Bonus: we'll also share the story on how we added the Babelfish support in DBeaver using the JDBC driver from Microsoft.

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.

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.

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.