PGConf.Russia 2018

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

I would like to share experience in runing PostgreSQL in dockerized environments, describe the specific issues and tools you will need to solve them.

• Which problems could be solved by Docker for PostgreSQL, e.g. PostgreSQLPro.9.6
• Work of IT team with Docker in development, testing and production environments
  • Using image repository and build servers for image testing
• Issues in production environment:
  • With network activity
  • With persistent repositories for Docker
  • With additional services
  • With load balancing and fail-safety
• Running PostgreSQL-base applications, such as:
  • SonarQube
  • Gitlab
  • 1С platform

MQTT is an effective data exchange protocol for IOT devices. Based on own modified EMQTT plug-in, the IoT project architecture uses PostgreSQL as a central processing and storing system for data coming from sensors in real time. The report will provide an example of the IoT hardware and software platform solution, based up on the MQTT protocol, where PostgreSQL is responsible for key functionality, providing processing, collecting and storage of data from a distributed network of IoT devices.

In the pitch I will talk about the most important nuances of deployment and operations of the distributed analytical open-source database based on PostgreSQL - Greenplum. I will analyze the typical mistakes in its use, give the best practices and warn about bottlenecks.