Apache Storm Vs Spark Streaming

What when and how to choose a real-time processing framework in a telecom scenario. Identified issues, potential problems and proposed solutions.

In two previous blog posts – and – I compared Apache Storm and Apache S4. In this post, I will present my comparison between Apache Storm and Spark Streaming.

Apache Storm is a stream processing framework, which can do micro-batching using Trident (an abstraction on Storm to perform stateful stream processing in batches).

Spark is a framework to perform batch processing. It can also do micro-batching using Spark Streaming (an abstraction on Spark to perform stateful stream processing).

I described the architecture of Apache storm in my previous post[1]. A detailed description of the architecture of Spark & Spark Streaming is available .

One key difference between these two frameworks is that Spark performs Data-Parallel computations while Storm performs Task-Parallel computations. More similarities and differences are given in the table below.