Real-Time Big Data Analytics with Storm

This talk provides an overview of the open source Storm system for processing Big Data in realtime. The talk starts with an overview of the technology, including key components: Nimbus, Zookeeper, Topology, Tuple, Trident. The presentation then dives into the complex Big Data architecture in which Storm can be integrated. The result is a compelling stack of technologies including integrated Hadoop clusters, MPP, and NoSQL databases.

The presentation then reviews real world use cases for realtime Big Data analytics. Social updates, in particular real-time news feeds on sites like Twitter and Facebook, benefit from Storm’s capacity to process benefits from distributed logic of streaming. Another case study is financial compliance monitoring, where Storm plays a primary role in reducing the market data to a useable subset in realtime. In a final use case, Storm is crucial to collect rich operational intelligence, because it builds multidimensional stats and executes distributed queries.

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