Using several example microservice applications, I'll compare and contrast using Akka Streams and Kafka Streams for stream processing with Kafka as the data "backplane". I'll discuss the strengths and weaknesses of each tool for particular design needs, so you'll feel better informed when making choices. I'll also contrast them with Spark Streaming and Flink, including when to chose them instead. For example, Akka and Kafka Streams are applications you embed in your microservices, while Spark and Flink are services to which you submit jobs to perform.
Dean Wampler, Ph.D., is the VP of Fast Data Engineering at Lightbend. He leads the development of Lightbend Fast Data Platform, a distribution of scalable, distributed stream processing tools including Spark, Flink, Kafka, and Akka, with machine learning and management tools. Dean is the author of several books, a frequent conference speaker and organizer, and he helps run several Meetups in Chicago.