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.

• the architecture
• the design and implementation of PL/pgSQL
• the difference between PL/SQL and PL/pgSQL
• the advantage and issues of PL/pgSQL

Unlike most other databases, PostgreSQL is developed by a community, and not by a company or even a foundation. Those who have been members of this community for a long time generally consider this a strength, but it can often be confusing to outsiders who are more used to dealing with traditional organization. For those who are not already on the inside, this talk will give an introduction to how the PostgreSQL community works and how the different parties interact, as well as how this has evolved over the years.

Schema-less is definitely a trend in the data storage nowadays, and it's not only about NoSQL, but also about traditional RDBMS. Many relational databases (e.g. PostgreSQL, Oracle, db2, Mysql) allow to storing data in the schema-less json format and use their own more or less unique way to do that.

This talk contains two parts:

• Comparison of the json support in PostgreSQL and different relational databases, namely Mysql, Oracle, db2, MSSql in terms of supported features, functions and so on.
• Performance benchmarks for databases with the advanced json support, namely PostgreSQL and Mysql, and the MongoDB on different workload types and configurations.