PgConf.Russia 2019

PostgreSQL provides possibility to create temporary tables. Though a temporary table is accessible only to a single session and is removed at the end of the session, all information about it is stored in the system catalogs of PostgreSQL. This is related to several issues, which make it difficult or impossible to use temporary tables in some cases. There are attempts to solve this feature, including in our company. But they have not yet succeeded, mainly because of the PostgreSQL engine. In the talk I want to tell about simple and small pg_variables extension. It allows you to create table variables along with scalar ones. I will tell how it can replace temporary tables, what advantages and disadvantages it has.

In this session we will deep dive into the exciting features of Amazon RDS for PostgreSQL, including new versions of PostgreSQL releases, new extensions, larger instances. We will also show benchmarks of new RDS instance types, and their value proposition. We will also look at how high availability and read scaling works on RDS PostgreSQL. We will also explore lessons we have learned managing a large fleet of PostgreSQL instances, including important tunables and possible gotchas around pg_upgrade.

As an experienced Oracle DBA, I've discovered some distinctive features of PostgreSQL which I'd like to share with you. We'll review a set of essential tools for DBAs, their capabilities and usefulness in comparison to their Oracle counterparts. Also I'm going to summarize the core differences between Oracle DB and PostgreSQL in terms of administrating.

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.