PgConf.Russia 2016

When new versions of Postgres are released most of the attention is focused on new features. Inevitably a release note claiming speed improvements seems relatively mundane and doesn't provide the compelling argument for upgrading. However the reality is that these speed improvements represent pain points that have been identified and solved.

Reviewing the changes to the sort code in Postgres over the last 10 years clearly shows the kinds of problems users have run into. As usage patterns changed over years, databases scaled up, and hardware changed new problems arose and drove further development to solve them.

Upcoming changes in 9.5 and 9.6 will dramatically change the experience further. Making sorting UTF8 and other encodings less of a problem and handling scaling to larger machines with many processors and memory cache more effectively.

CitusDB is an extension for PostgreSQL that can distribute tables across a cluster of PostgreSQL servers. Data is stored in shards that can use append-partitioning for bulk-loading of time series data or hash-partitioning for real-time data ingestion. SELECT queries on distributed tables are transparently parallelised across the cluster, using all available cores. Distributed tables can also be joined in parallel, even if they are not partitioned along the same column. CitusDB is especially suitable for real-time analytics use-cases such as dashboards which require fast analytical queries over live data, and can simultaneously act as a scalable operational database. This talk will describe the internals of CitusDB and give a live demo of a large-scale CitusDB cluster.

First working on Oracle, we could not ignore appearance and growth of PostgreSQL. I will describe how we came to PostgreSQL and share some experience of migrating a large medical system.

• developing a code converter;
• packages migration;
• our patches solving some of the migration problems.