Streaming ETL in Practice with PostgreSQL, Apache Kafka, and KSQL

A presentation at Postgresconf NYC in in New York, NY, USA by Viktor Gamov

Have you ever thought that you needed to be a programmer to do stream processing and build streaming data pipelines? Think again!

Companies new and old are all recognizing the importance of a low-latency, scalable, fault-tolerant data backbone, in the form of the Apache Kafka® streaming platform.

With Kafka, developers can integrate multiple sources and systems, which enables low latency analytics, event-driven architectures and the population of multiple downstream systems.

These data pipelines can be built using configuration alone.

In this talk, we’ll see how easy it is to stream data from a database such as PostgreSQL into Kafka using CDC and Kafka Connect.

Besides, we’ll use KSQL to filter, aggregate and join it to other data, and then stream this from Kafka out into multiple targets such as Elasticsearch and S3.

All of this will be accomplished without a single line of code!

Why should programming buffs have all the fun?


The following resources were mentioned during the presentation or are useful additional information.

  • Demos

    This demo shows how to enrich event stream data with CDC data from Postgres and then stream into Elasticsearch.


The following code examples from the presentation can be tried out live.