PgConf.Russia 2019

As we all know, PostgreSQL is a classic vertically scalable database for OLTP loads. In parallel with PostgreSQL for many years there is its alternative horizontal-scalable MPP version of PostgreSQL, that is called Greenplum, sharpened for big data and OLAP workload. In my pitch I will show the internal architecture of Greenplum (distributed transactions, data sharding, partitioning with hybrid storage in external systems, column storage engines with compression, and much more), a comparison with the internal structure of PostgreSQL and the application areas of each solution are shown.

Shared_buffers = 25% – is it too much or not enough? Or it's the right value?

How can we ensure that this – pretty much outdated – recommendation suit well our needs?

It is time to start apply enterprise-level approach to tuning postgresql.conf. Not using various blind auto-tuners or advices from old articles and blog posts, but based on the following two aspects:

1. comprehensive database experiments, conducted in automated fashion, repeated multiple times in conditions as close to production as possible, and
2. deep understanding of DBMS and OS internals.

Using Nancy CLI (https://gitlab.com/postgres.ai/nancy) we will consider a concrete example: infamous shared_buffers, under various circumstances, in various projects. We will try to figure out, how to optimize this settings for given infrastructure, database, and workload.

As any ordinary software developers, we just pursued a goal to develop a system robust for high loads, and even succeeded. The system architecture was fine, but the data volume was keeping increased and revealed the painful issues and errors that nobody had expected. We faced very strange queries seemed to be unbelievable. In my short talk I would like to share sad experience of arised-from-nothing high loads in DBMS and solving the challenge.

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.