PGConf.Russia 2018

I would like to share experience in runing PostgreSQL in dockerized environments, describe the specific issues and tools you will need to solve them.

• Which problems could be solved by Docker for PostgreSQL, e.g. PostgreSQLPro.9.6
• Work of IT team with Docker in development, testing and production environments
  • Using image repository and build servers for image testing
• Issues in production environment:
  • With network activity
  • With persistent repositories for Docker
  • With additional services
  • With load balancing and fail-safety
• Running PostgreSQL-base applications, such as:
  • SonarQube
  • Gitlab
  • 1С platform

In the pitch I will talk about the most important nuances of deployment and operations of the distributed analytical open-source database based on PostgreSQL - Greenplum. I will analyze the typical mistakes in its use, give the best practices and warn about bottlenecks.

Pluggable storages is hot subject in PostgreSQL development. The period of heated debates about whether we need them is over. Skepticism about pluggable storages, based on concern that they may be source of inconsistent behavior, was weakened after criticism of PostgreSQL MVCC implementation from Uber side. It became widely understandable that pluggable storages are needed at least for an alternative MVCC implementation. And that is one of way-points for pluggable storages interface design.

At the moment, work on pluggable storages is in the practical stage. There is a thread is pgsql-hackers where few people are developing patchset and several people are doing review.

This talk will cover following subjects:

• overview of pluggable storages interface;
• changes in PostgreSQL core required to implement this interface;
• current and potential implementations of pluggable storages including heap with undo-log and in-memory OLTP engine;
• current state of patchset and prospective of its commit
• further development of interface allowing more possibilities in pluggable storages (columnar, index-organized, LSM and so on).

PostGIS is a spatial extension to PostgreSQL that enables spatial datatypes, access methods and a set of functions to perform geometric operations on them.

Typically PostGIS is used to select a small subset of a big static dataset. In this talk I'll cover issues that arise when working with big dynamic data flows, and ways to resolve them, on examples that we've met developing Juno ride sharing service backend.