PgConf.Russia 2017

Alexey will present technical details and share hands-on experience of extreme data normalization application for data infrastructure with exceptional parameters design and development. Extreme normalization-based data infrastructures has the following competitive advantages in comparison with market leaders: - Real-time data processing for 10 PB of data and more - 2-6 times better overall performance - 100% data consistency through total data landscape - Almost linear scalability - 4-10 lower cost of ownership - etc The abovementioned approach has been successfully utilized out of Russian market in telecommunication, retail, fin-tech, manufacturing (Industry 4.0, industrial IoT), and government institutions.

VIDEO

Debugging, profiling, and tracing of the executed commands play an important role in development of any applications. This is also true for developing stored procedures in DBMS.

PostgreSQL offers various tools (both built-in and external) for these purposes.

In this talk, we will provide an overview of the available tools and their advantages and disadvantages, as well as a detailed demo of their use cases.

This talk is a part of a basic course for backend application developers (DEV1), which “Postgres Professional” company plans to announce in the near future.

Citus allows you to distribute postgres tables across many servers. It extends postgres to transparently delegate or parallelise work across a set of worker nodes, enabling you to scale out the CPU and memory available for queries.

One year ago, we began a long journey to allow Citus to scale out another dimension: write throughput. With writes being routed through a single postgres node, write throughput in Citus was ultimately bottlenecked on the CPUs of a single node. Citus MX is a new edition of Citus which allows distributed tables to be used from from any of the nodes, enabling NoSQL-like write-scalability.

I love complex knowledge domains, strong typing in applications, and 3NF, but I hate ORM. That is why I’ve been actively storing serialized structures in JSON fields (even before the JSON type was introduced). In this talk, I will tell you about some specifics of storing complex structures within DBMS fields, what problems can arise, and how to cushion the blow.

VIDEO