Sessions at Strange Loop 2011 about NoSQL and Real Time with notes and slides

Monday 19th September 2011

• Storm: Twitter's scalable realtime computation system

  by Nathan Marz

  Storm makes it easy to write and scale complex realtime computations on a cluster of computers, doing for realtime processing what Hadoop did for batch processing. Storm guarantees that every message will be processed. And it’s fast — you can process millions of messages per second with a small cluster. Best of all, you can write Storm topologies using any programming language.

  Storm has a wide range of use cases. The basic use case is “stream processing”: processing a stream of new data and updating databases in realtime. Unlike the standard approach of doing stream processing with queues and workers, Storm is fault-tolerant and scalable.

  Another use case is “continuous computation”: streaming the results of a query to clients to visualize in realtime. An example is streaming trending topics on Twitter into browsers.

  A third use case is “distributed RPC”: computing an intense query on the fly in parallel. With distributed RPC, a Storm topology is a distributed function that you can invoke like a normal function.

  In this talk, I’ll release Storm as open-source. I’ll show how Storm’s simple programming model makes realtime computation easy, robust, and even fun.

  • Big Data
  • NoSQL
  • Real Time
  • Twitter

  At 10:30am to 11:20am, Monday 19th September

  In Grand Ballroom, Hilton St. Louis at the Ballpark

  Coverage slide deck note