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

It often happens that you already have PosgtreSQL in production, but you don’t have a DBA. To demystify the PostgreSQL database, I’ll tell you how to troubleshoot various problems while working with PosgtreSQL. We will try to understand how to answer "routine" questions of a typical system administrator: - Is everything OK with the database? - What consumes DB server resources? - What to optimize first to reduce resource consumption?

VIDEO

MongoDB is a successful database in the NoSQL space, mostly used for OLTP-type workloads. However, due to the lack of ACID (transactions in particular) and significant performance issues with OLAP/DW workloads, more and more MongoDB users are considering migrating off of MongoDB to a RDBMS, where PostgreSQL is the usual choice. This represents a significant opportunity for the PostgreSQL ecosystem, to "bring NoSQL to SQL". This talk will present the challenges that MongoDB users are facing and the state of the art of the available tools and open source solutions available to perform ETL and live migrations to PostgreSQL. In particular, ToroDB Stampede will be discussed, an open source solution that replicates live from MongoDB, transform JSON documents into relational tables, and stores the data in PostgreSQL.

VIDEO

The talk will describe how we have implemented storage of large tables (+1 billion rows per day). The project exists in production 2 years. The total amount of data - 300 Tb (25 PostgreSQL servers * 2 Data Center). I'll tell about mistakes in organization of large tables storage in the initial phase of the project, and how these mistakes were corrected. I'll also talk about how to organize the data rotation and archiving. I voiced questions about what we were missing in PostgreSQL 9.4 out of what appeared in the 9.5 and 9.6. And also, what new features we are waiting for new releases of PostgreSQL.