PgConf.Russia 2019

So you finally have your database model for your application and you fill it in with current data. How do you keep it up to date? While INSERT may still be transparent, UPDATE and DELETE will overwrite your previous data, so you won't be able to reproduce them. Cloning the whole huge content for each minor update is not an option. For rich and complex data about hundreds of thousands of power generators in Germany and worldwide, I built a model using range data types in recent PostgreSQL which allows me to insert, update and delete data while granting the full access to the whole state of the database at any historical moment. I'll present a very simplified version of the database so the audience will be immediately able to apply it for their cases. I'll also show a few tricks in Python and Psycopg2 that will allow a whole team to prepare, review, and deploy all revisions to this database without merge conflicts. And I'll give a few ideas on how to retrieve this data efficiently.

Patroni is getting art of state standard framework for building HA clusters with postgres now.

During session we will build simple 3 node cluster using mentioned stack.

We will discuss patroni's architecture, and most interesting parameters from it's configuration. We will check how actually failover works and how could you initialise cluster.

After session you will be able to built such cluster from scratch in minutes using given ansible playbooks.

In this tutorial we will discuss Binary and Logical replication in a practitioner format. The topics that will be included are native Postgres replication technologies, configuring and managing them. We will also discuss performance and draw backs of various architectures (sync vs async etc...). At the end of this presentation the attendees will be able to configure a basic replication deployment with HOT Standby and well as have an understanding of other technologies such as Point in Time Recovery and cascading replication.

Reliable backup and recovery, at enterprise level for the PostgreSQL environment. No more traditional backups. CBT (Change Block Tracking) technology is the next generation incremental backup. Faster than snapshots, CBT back up blocks that change, not all of your data, reducing server and network traffic and eliminating the need for traditional backups. Benefits: • Data protection mode close to Real-Time • Update with ease