PGConf.Russia 2018

In this talk, I will tell you the story of how a bunch of sysadmins got sick of having to resuscitate their petabyte-sized Elasticsearch cluster and decided to replace it with some tried technologies: PostgreSQL, Kafka, a bit of Redis, lots of glue, and the typical sysadmin stubbornness. The result is Bagger: the sysadmin answer to Big Data. A fast, fairly reliable, fault-tolerant store, used mostly for logging timestamped events for some amount of time. Bagger is named the Bagger series of bucket-wheel excavators, feats of German engineering and some of the largest land vehicles ever produced by man. Just like the excavators that dig through tons of material, our Bagger digs through tons data.

Postgres has a nice feature called Point-in-time Recovery (PITR) that would allow you to go back in time. In this talk, we will discuss what are the use-cases of PITR, how to prepare your database for PITR by setting good base backup and WAL shipping setups, with some examples. We will expand the discussion with how to achieve PITR if you have a distributed and sharded Postgres setup by mentioning challenges such as clock differences and ways to overcome them, such as two-phase commit and pg_create_restore_point.

The report reviews approaches and implementattion options for the migration of Parus-Budget 8 client-server application from the Oracle Database platform to the PostgreSQL platform without changing the client application for Desktop and the Web. The proposed solution allows to make transparent transition of the existing users' workplaces.