PgConf.Russia 2020

Today no one is surprised by cloud infrastructure anymore, but not all its components are easy to deploy in cloud. For example, the database is always very demanding in terms of performance and resources. Scaling and fault tolerance are the most acute problems, that's why we have been observing rapid development of alternative DBMS in the recent years. However, traditional relational DBMS have already accumulated a lot of various features, so they often remain the first choice. Besides, they are constantly evolving and offer a wide variety of scaling tools. I will mainly speak about PostgreSQL, when you should consider scaling, and how to do it right.

We will touch upon the following topics:
- Streaming replication and balancing read/write workloads
- Logical replication and data sharding
- High availability and fault tolerance

This talk should be interesting to DBAs, system administrators, team leads, infrastructure architects, as well as wider audience dealing with PostgreSQL.

Odd things in query plan analysis - wasted time and "unnecessary" buffers.
Structural hints in a plan. How to help a developer with optimization without writing a single line of code. How to match plan nodes with query text and take advantage of this information.

Sometimes it maybe a very tricky just to establish a connection with your remote database. Especially if your working place is in highly secured corporate environment and your database server is in highly secured remote cloud.

We will talk about bypassing SSH, SSL, jump servers, proxy servers, VPNs and various SSO (Kerberos/SSPI/LDAP/Active Directory) authentication systems in order to access your PostgreSQL database using console or rich UI interface and JDBC. We will describe different use cases - from trivial and typical to insane and over-secured.

I'll show an example of solving the problem of searching "similar" texts for one given text in big array using GiST index. The problem itself is not much important, but it is easy to understand. Using this problem as example, I'll show one of many methods of adapting GiST index for custom search problems. Maybe this talk will help you to solve other search problems.