PGConf.Russia 2018

One of advantages of document-oriented databases like MongoDB or Couchbase over RDBMSs is an ability to change the data scheme easily, fast and often. The traditional approach in RDBMS world involves doing an expensive ALTER TABLE operation, slow upgrade of an existing data, and stuff like this. This approach is often slow and inconvenient for application developers.

To solve this issue PostgreSQL provides JSON and JSONB datatypes. Also there are extensions like zson and pg_protobuf. From this talk you will learn how to work with these datatypes and extensions, their pros and cons and also related future work in this area.

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.

Comparison of capabilities of PostgreSQL and MS SQL to work with 1С. What does pg_restore mean for 1С user? Results of load testing for 1C database of more than 1TB size. The story of one 1C Production: 2 years, 500+ databases 1C, 4TB of data, cascading replication.