Big data analytics on high Velocity streams: A case study

Big data management is often characterized by three Vs: Volume, Velocity and Variety. While traditional batch-oriented systems such as MapReduce are able to scale-out and process very large volumes of data in parallel, they also introduce some significant latency. In this paper, we focus on the second V (Velocity) of the Big Data triad; We present a case-study where we use a popular open-source stream processing engine (Storm) to perform real-time integration and trend detection on Twitter and Bitly streams. We describe our trend detection solution below and experimentally demonstrate that our architecture can effectively process data in real-time - even for high-velocity streams.