Real-time processing is becoming very popular, and Storm is a popular open source framework and runtime used by Twitter for processing real-time data streams. Storm addresses the complexity of running real time streams through a compute cluster by providing an elegant set of abstractions that make it easier to reason about your problem domain by letting you focus on data flows rather than on implementation details.
Storm has many use cases: realtime analytics, online machine learning, continuous computation, distributed RPC, ETL, and more. Storm is fast: a benchmark clocked it at over a million tuples processed per second per node. It is scalable, fault-tolerant, guarantees your data will be processed, and is easy to set up and operate.
This pattern integrates XAP with Storm. XAP is used as stream data source and fast reliable persistent storage, whereas Storm is in charge of data processing. We support both pure Storm and Trident framework.
As part of this integration we provide classic Word Counter and Twitter Reach implementations on top of XAP and Trident.
Also, we demonstrate how to build highly available, scalable equivalent of Realtime Google Analytics application with XAP and Storm. Application can be deployed to cloud with one click using Cloudify.
Sources are available on github