PgConf.Russia 2017

I will tell you about why Postgres is first-choice product as a foundation for your BI system with classical OLAP workload. Briefly it will be said about existing open source BI solutions.

I will also describe specific of our architecture, why we chose snowflake scheme and how we are doing extract, transformation and load procedures. It will be mentioned about special Postgres tuning for OLAP and massive data bulkload workloads. Also I will let you know about Postgres usage as a column database with cstore_fdw by Citus and results achieved. Cons and problems of our approach will be described in the end of the talk.

VIDEO

The report is focused on the topic of automation of migration to PostgreSQL from other databases using Ispirer Migration and Modernization Toolkit. The issues of data and SQL code migration, conversion of client applications, embedded SQL and database API will be covered, the examples of implemented projects of migration from Oracle to PostgreSQL and from Microsoft SQL Server to PostgreSQL will be given.

VIDEO

PostGIS enables spatial processing in Postgres. Usually PostGIS is used for planar euclidean calculations, but real world adds time, ambiguity and uncertainty. We'll have a look on making a thousand of cars move smoothly in real time on OpenStreetMap base map.

VIDEO

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.