PgConf.Russia 2017

Database systems are increasing in size and so is the need to process huge amounts of data in real time. As commercial database vendors are bragging about their capabilities we decided to push PostgreSQL to the next level and exceed 1 billion rows per second to show what we can do with Open Source. To those who need even more: 1 billion rows is by far not the limit - a lot more is possible. Watch and see how we did it.

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This talk is intended for Oracle DBAs whose are considering to start using PostgreSQL as another RDBMS engine in their DB portfolio or for PostgreSQL DBAs, who wants to learn some of similarities and differences between Oracle and PostgreSQL. This talk is not intended to be a migration guideline neither advocating one platform over another. General database structure overview for both platforms will be compared in terms of memory configuration parameters; logical to physical structure as well as we’ll touch some security point of view and backup & recovery tools available. Oracle container databases are not covered. The talk want’s to help create a bridge for DBA and avoid some frustrations at the first Oracle DBA step to discover, learn and start using PostgreSQL as reliable fully functional database.

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Input-output (IO) performance issues have been on DBAs’ agenda since the beginning of databases. The volume of data grows rapidly and time is of an essence when one needs to get necessary data fast from the disk and, more importantly, to the disk.

For most databases it is relatively easy to find checklist of recommended Linux settings to maximize IO throughput and, in most cases, this checklist is indeed good enough. It is however essential always to understand how the optimisation of those settings actually works, especially, if you run into corner cases.

Partitioning is a long-awaited feature in PostgreSQL. Although Postgres supports partitioning via inheritance, this approach has some disadvantages, such as the need to manually create partitions and support triggers, significant planning overhead, and no query execution optimizations. In this talk, we’ll tell you about the pg_pathman extension we are developing. pg_pathman supports HASH and RANGE partitioning, performs planning and execution optimizations, supports fast insert by using Custom Node instead of triggers, provides functions for partition management (add, split, merge, etc.), supports FDW, non-blocking data migration, and more. We'll also speak about pg_pathman integration with Postgres Pro Enterprise Edition and Oracle-like syntax support for partitioning. Finally, we'll discuss new partitioning capabilities in PostgreSQL 10, the already implemented features and further development plans.

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