PgConf.Russia 2020

Recently, I was working on a project where graphQL was used for sending requests to its .NET Core backend, but this was not a good idea. The point is, a graphQL query is a hierarchical structure with a dynamic set of fields. It’s difficult to perform such requests via a statically-typed programming language and a relational database as suggested by the tools available. So, I came up with the idea of using the plv8 extension and perform graphQL queries right on the database side. It took me about two hours to develop a working prototype that could perform the same queries as the software under development for more than one month! Then various improvements have been made and I want to introduce them all. If you are thinking of using graphQL instead of REST, my speech could be most useful and could help you to save a lot of time.

This talk discusses the open source components we use at Adjust to manage a massive number (5+PB) of application log messages on PostgreSQL in a massively multi-parallel way. It provides both a use case for PostgreSQL in a big data (high volume/velocity/variety) environment, and can be used to show the power of PostgreSQL with JSONB, GIN, and more.

This talk covers the capabilities of the components in depth, sufficient to inspire similar solutions.

PostgreSQL built-in full text search gives unique possibilities inaccessible for external search engines, such as virtual or generated document search and search with access restrictions. I will talk about these and other features, full text search configuration, indexes, and highlight the latest advances and future expectations

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.