In the past few years Apache Kafka has established itself as the world's most popular real-time, large-scale messaging system. It is used across a wide range of industries by thousands of companies such as Netflix, Cisco, PayPal, Twitter, and many others.
In this session I am introducing the audience to Kafka Streams, which is the latest addition to the Apache Kafka project. Kafka Streams is a stream processing library natively integrated with Kafka. It has a very low barrier to entry, easy operationalization, and a high-level DSL for writing stream processing applications. As such it is the most convenient yet scalable option to process and analyze data that is backed by Kafka. We will provide the audience with an overview of Kafka Streams including its design and API, typical use cases, code examples, and an outlook of its upcoming roadmap. We will also compare Kafka Streams' light-weight library approach with heavier, framework-based tools such as Apache Storm and Spark Streaming, which require you to understand and operate a whole different infrastructure for processing real-time data in Kafka.