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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Sets are apparently a useful data type for many kinds of applications. While PostgreSQL offers no built-in set data type, sets may be emulated to some degree with its built-in array and JSONB data types. Also, acceleration of respective containment (subset) queries is readily available as a built-in feature of the GIN index type.

Starting with the above, we will then explore the performance gains enabled by custom set data types, and especially by customisation code in C ("operator classes") for the GIN and GiST index types.

It's not a secret that PostgreSQL connections are expensive so you should save them. To solve this problem there are PgPool-II and PgBouncer for quite a long time. At Yandex tens of thousands of connections to a single database is not a surprise so we use pgbouncer since time immemorial. This talk gives an overview of problems we faced and ways to solve them.

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