PgConf.Russia 2016

PostgreSQL includes several index types: GiST, SP-GiST, GIN, and of course, the regular B-tree. DBAs are familiar with using each of these for specific use cases, GIN for full-text search, GiST for geometrical data, and so on, but how do they work internally? What makes them suitable for the cases they're typically used for?

In this presentation, I will walk through the internal structure of each of these index types, explaining what strengths and weaknesses each one of them have.

The Korean PostgreSQL User Group has been relatively small and inactive for many years. However, recently things are changing in Korea. Companies are seeking to alternatives for their expensive proprietary RDBMS in order to cut their TCO. And the government institutes also participate in this trend. We, Bitnine, are leading these changes in Korea. We launched the first version of our PostgreSQL solution, Agens SQL in 2015. We are translating the PostgreSQL documentation into Korean and operating the PostgreSQL User Group. And we are trying to contribute the PostgreSQL Global Development Group. Also, the first Korean PostgreSQL Conference will be hold in 2016. We will lead the organization of this conference. In this talk, we will present the current status of the Korean PostgreSQL User Group and the PostgreSQL DBMS market in Korea. And we also present our activities in Korea and introduce our successful migration cases of the proprietary RDBMS into PostgreSQL.

A year passed after birth of Postgres Pro, the Russian PostgreSQL company. The talk will describe the main achievements of the year are the future plans, including development, certification, russian documentation translate, education program.

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.