Acca Street vs. Spark Stream

Question

What are the advantages / disadvantages of using an aka stream against a spark stream to process a stream? e.g. built-in back pressure, performance, fault tolerance, built-in transformation, flexibility, etc. I DO NOT ask for acc against spark pros / cons of strictly streaming component. In addition, I am NOT asking about the difference in the architecture of the hood infrastructure.

Answer 1

Streams of Akka and Spark from two different lands. Do not let the word "flows" confuse you.

Akka streams implement something called a reactive manifest, which is great for achieving really low latency and provides many operators that can easily write declarative conversions over streams. Read more about this at https://doc.akka.io/docs/akka/2.5.4/scala/stream/stream-introduction.html#motivation .

Spark Streaming aka Structured Streaming as of 2.2 is still a micro-packet approach for processing huge amounts of data (Big Data). Collections are collected and then processed periodically in small batches every few seconds.

Akka streams are mostly not distributed and do not scale across clusters, unlike Spark.Akka streams, Akka's promotional model is used to achieve Concurrency.

Akka streams is the toolkit, and Spark is the foundation. PS: Even I had the same question a couple of months ago. It took a while to get the answers. Hope this will be helpful.