PgConf.Russia 2016

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.

Since its launch in 2008, Zalando has grown with tremendous speed. The road from startup to multinational corporation has been full of challenges, especially for Zalando's technology team. Distributed across Berlin, Helsinki, Dublin and Dortmund — and nearly 900 professionals strong — Zalando Technology still plans to expand by adding 1,000 more developers through the end of 2016. This rapid growth has showed us that we need to be very flexible about developing processes and organizational structures, so we can scale and experiment. In March 2015, our team adopted Radical Agility: a tech management strategy that emphasizes Autonomy, Purpose, and Mastery, with trust as the glue holding it all together. To make autonomy possible, teams can now choose their own technology stacks for the products they own. Microservices, speaking with each other using RESTful APIs, promise to minimize the costs of integration between autonomous teams. Isolated AWS accounts, run on top of our own open-source Platform as a Service (called STUPS.io), give each autonomous team enough hardware to experiment and introduce new features without breaking our entire system.

One small issue with having microservices isolated in their individual AWS accounts: Our teams keep local data for themselves. In this environment, building an ETL process for data analyses, or integrating data from different services, becomes quite challenging. PostgreSQL's new logical replication features, however, now make it possible to stream all the data changes from the isolated databases to the data integration system so that it can collect this data, represent it in different forms, and prepare it for analysis.

In this talk, I will discuss Zalando's open-source data collection prototype, which uses PostgreSQL's logical replication streaming capabilities to collect data from various PostgreSQL databases and recreate it for different formats and systems (Data Lake, Operational Data Store, KPI calculation systems, automatic process monitoring). The audience will come away with new ideas for how to use Postgres streaming replication in a microservices environment.

We'll discuss how does Linux work with virtual memory. The following topics will be covered: * x86-64 page table, context switch and page fault; * internals of virtual memory management (VMM) in Linux; * page eviction methods in Linux, page cache and anonymous pages; * huge and gigantic pages, transparent huge pages; * how mmap(2) works and what madvise(2), msync(2) etc. provide; * why large databases don't use mmap(2), but rather implement buffer pool on their own; * ans surely how to tune Linux VMM using sysctl.