Streaming Microservices with Akka Streams and Kafka Streams

Kafka Streams is purpose built for reading data from Kafka topics, processing it, and writing the results to new topics. With powerful stream and table abstractions, and an exactly once capability, it supports a variety of common scenarios. Akka Streams emerged as a dataflow-centric abstraction for the Akka Actor model, designed for general-purpose microservices and very low-latency event processing. It supports a wider class of application problems and third-party integrations, so it’s less Kafka-centric. In this webinar, Dean will: Discuss the strengths and weaknesses of Kafka Stream and Akka Streams for particular design needs in data-centric microservices, so you’ll feel better informed when making choices. Contrast them with Spark Streaming and Flink, which provide richer analytics over potentially huge data sets where scalability through “automatic” partitioning is required, so you can determine when to choose them instead.