PgConf.Russia 2019

PostgreSQL 12 Feature Freeze is scheduled for April 2019, which didn't come yet. But general shapes of upcoming release are already visible. In this talk I'll consider patches already committed to PostgreSQL 12 as well as patches, which would be committed very likely. I'll talk with special passion about SQL/JSON, Merge, pluggable table access methods and zheap.

You just set up your first PostgreSQL cluster, created a database schema, loaded some data, did some fine tuning of configuration. Now you want to make your cluster highly available. Unfortunately, PostgreSQL doesn't offer built-in automatic failover, but luckily for us, there are plenty of external tools for that. As a next logical step you start choosing a tool, and... you already doing it wrong, because first you have to define SLA, RTO, and RPO. In this talk I am going to cover most of the common mistakes people do when setting up a highly available cluster.

Managed database services are gaining in popularity. In this session we look at how best to configure Amazon RDS for PostgreSQL and also look at common user operations of using RDS for PostgreSQL. We will also look beyond common user operations and into some specific optimizations related to upgrade, logical replication, performance, and reducing downtime.

At pgconf’17 I talked about our analytics systems based on PostgreSQL. Afterwards we looked at hadoop, s3, presto, vertica, and other frights. Finally we stopped to suffer nonsense and just completed PostgreSQL with ready Greenplum and Clickhouse. As a result, we achieved amazing performance, fast migration, easy maintenance, reliability and horizontal scalability. We enabled to recover the system after fault in two commands, decreased infrastructure costs and expanded functionality due to ANSI SQL, MPP and In-memory. All within the open-source and full SQL paradigm. We called the product GreenHouseSQL, which is our inner whole cycle data platform. In the talk we will show the beauty of solution internals, explain the advantages and flaws, tips and tricks of starting with Greenplum, as well as why do we need Clickhouse, what is left to PostgreSQL, and eventually how does it all work.