PGConf.Russia 2018

For over 15 years JetBrains have strived to make effective developer tools. IntelliJ IDEA for java is the most popular of them. IntelliJ supports databases as well, and finally we in JetBrains decided to bring this functionality and our experience in programming languages to the world of SQL. That’s how DataGrip appeared. In my talk I will tell how DataGrip helps developers by automating routine checks and corrections and speeds up developer’s production. I will also show how to extend IDE’s functionality and try to understand which actual problems we can solve in future.

One of advantages of document-oriented databases like MongoDB or Couchbase over RDBMSs is an ability to change the data scheme easily, fast and often. The traditional approach in RDBMS world involves doing an expensive ALTER TABLE operation, slow upgrade of an existing data, and stuff like this. This approach is often slow and inconvenient for application developers.

To solve this issue PostgreSQL provides JSON and JSONB datatypes. Also there are extensions like zson and pg_protobuf. From this talk you will learn how to work with these datatypes and extensions, their pros and cons and also related future work in this area.

If you honestly evaluate most of our business applications, you will see that they first collect and import the data into a database and then send the same data in the opposite direction.

What if we don't build an ORM wall between the application and the database, but try using the symbiosis of their strong points and special features instead?

I will tell you how we use PostgreSQL and Clojure for building data-intensive medical applications. We will cover the following topics:

• functional relational programming
• jsonb for modeling complex data domains
• functional indexes and json-knife extension for jsonb search
• graphql implementation on PostgreSQL
• logical replication for building reactive integrations
• asynchronous JDBC-free connector to PostgreSQL on netty

PostGIS is a spatial extension to PostgreSQL that enables spatial datatypes, access methods and a set of functions to perform geometric operations on them.

Typically PostGIS is used to select a small subset of a big static dataset. In this talk I'll cover issues that arise when working with big dynamic data flows, and ways to resolve them, on examples that we've met developing Juno ride sharing service backend.