At StampedeCon 2014, Scott Shaw (Hortonworks) and Kit Menke (Enteprise Holdings) presented "Storm – Streaming Data Analytics at Scale"
Storm’s primary purpose is to provide real-time analytics against fast moving data before its stored. The use cases range from fraud detection, machine learning, to ETL.
Storm has been clocked at over 1 million tuples processed per second per node. It’s fast, scalable, and language agnostic. This session provides an architecture overview as well as a real-world discussion of its use and implementation at Enterprise Holdings.