Akka vs Kafka: What are the differences?
Developers describe Akka as "Build powerful concurrent & distributed applications more easily". Akka is a toolkit and runtime for building highly concurrent, distributed, and resilient message-driven applications on the JVM. On the other hand, Kafka is detailed as "Distributed, fault tolerant, high throughput pub-sub messaging system". Kafka is a distributed, partitioned, replicated commit log service. It provides the functionality of a messaging system, but with a unique design.
Akka can be classified as a tool in the "Concurrency Frameworks" category, while Kafka is grouped under "Message Queue".
"Great concurrency model" is the top reason why over 22 developers like Akka, while over 95 developers mention "High-throughput" as the leading cause for choosing Kafka.
Akka and Kafka are both open source tools. Kafka with 12.7K GitHub stars and 6.81K forks on GitHub appears to be more popular than Akka with 10.1K GitHub stars and 3.04K GitHub forks.
According to the StackShare community, Kafka has a broader approval, being mentioned in 509 company stacks & 470 developers stacks; compared to Akka, which is listed in 76 company stacks and 57 developer stacks.
What is Akka?
What is Kafka?
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Front-end messages are logged to Kafka by our API and application servers. We have batch processing (on the middle-left) and real-time processing (on the middle-right) pipelines to process the experiment data. For batch processing, after daily raw log get to s3, we start our nightly experiment workflow to figure out experiment users groups and experiment metrics. We use our in-house workflow management system Pinball to manage the dependencies of all these MapReduce jobs.
we used akka as our concurrency system at talenthouse. had the chance to write several worker. we used both akka messaging and rabbitmq to communicate. quite a slick system, was fun writing it in scala.
Akka powers our asynchronous document upload processor, handling e.g. tasks for OCR, thumbnail generation and document analysis.
Building out real-time streaming server to present data insights to Coolfront Mobile customers and internal sales and marketing teams.