One of the most frequent questions that we at Lightbend have been asked is “what’s the difference between Akka Streams and Kafka Streams?” After all, there is only a 1 letter difference between these two technologies, so how different could they be?
Well, as we are about to learn, they are actually quite different. Both tools are part of Lightbend Fast Data Platform, but were created with entirely different technological approaches in mind. For example, Akka Streams emerged as a dataflow-centric abstraction for the Akka Actor model, designed for general-purpose microservices, very low-latency event processing, and supports a wider class of application problems and third-party integrations via Alpakka. Kafka Streams, by comparison, is purpose-built for reading data from Kafka topics, processing it, and writing the results to new topics in a Kafka-centric way.
In this webinar by Dr. Dean Wampler
, VP of Fast Data Engineering at Lightbend, we will:
- Discuss the strengths and weaknesses of Kafka Streams and Akka Streams for particular design needs in data-centric microservices, including code examples
from our Kafka Streams with Akka Streams tutorial.
- Contrast them with Spark Streaming and Flink, which provide richer analytics over potentially huge data sets
- Help you map these streaming engines to your specific use cases, so you confidently pick the right ones for your jobs
Watch The Full Presentation (~50 Min)