Today, companies regularly generate terabytes of data in their
daily operations. The sources include everything from data
captured from network sensors, to the Web, social media,
transactional business data, and data created in other business
contexts. Given the volume of data being generated, real-time
computation has become a major challenge faced by many
organizations. A scalable real-time computation system that we
have used effectively is the open-source Storm tool, which was
developed at Twitter and is sometimes referred to as "real-time
Hadoop." However, Storm is far simpler to use than Hadoop in
that it does not require mastering an alternate universe of new
technologies simply to handle big data jobs. This article
explains how to use Storm. The example project, called "Speeding
Alert System," analyzes real-time data and raises a trigger and
relevant data to a database, when the speed of a vehicle exceeds
a predefined threshold. Whereas Hadoop relies on batch
processing, Storm is a real-time, distribu