PgConf.Russia 2017

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.

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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.

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Input-output (IO) performance issues have been on DBAs’ agenda since the beginning of databases. The volume of data grows rapidly and time is of an essence when one needs to get necessary data fast from the disk and, more importantly, to the disk.

For most databases it is relatively easy to find checklist of recommended Linux settings to maximize IO throughput and, in most cases, this checklist is indeed good enough. It is however essential always to understand how the optimisation of those settings actually works, especially, if you run into corner cases.