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.

Everyone has heard something about transaction isolation levels, but oddly enough, almost no one can clearly explain what it is any why it is important. At the same time, for many operations, it is critical to have a clear understanding of isolation levels and how they can affect the result. Indeed, if a customer has been paid twice and the developer has to pay back the losses, it won't seem unimportant. We'll discuss how to avoid such unpleasant situations.

From the very beginning, PostgreSQL in Avito has been solving very important tasks. All the main architecture components are built around DBMS. For over 10 years, the project has been actively evolving, and the infrastructure and architecture have changed a lot.

The talk will start with an overview of how PostgreSQL infrastructure and architecture have advanced in Avito over time and which challenges have been successfully resolved.

Then we'll discuss PostgreSQL usage scenarios in Avito in 2020: microservice architecture, sharding, hosting multiple databases on a single server instance, DBaaS (Database discovery, access control, failover, backup, archive, resource sharing, etc.), integration, and team evolution.
And finally, I'll share our backlog and wishlist.

It is our experience of the medical information system "RT MIS" transfer from MSSQL to PostgreSQL . When the necessity of transfer to PostgreSQL in our "RT MIS", one of the largest medical information systems, became imminent, we felt really terrified having assessed its amount: there was a huge number of stored procedures, functions, SQL-queries in its application code and services. It all requested transcribing, was exacerbated by demands on the system accessibility. So the variant "we awoke in the morning and PostgreSQL was working everywhere" was definitely impossible. That is why we chose another way: began eating "the elephant (PostgreSQL)" in chunks.

In my report, I am going to share our practical experience of the transfer, the instruments we used, the reason for another replication, the problems we met and their solutions. And finally, what turned out to be better: PostgreSQL or MSSQL.