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"Here's a recap of the three broad use cases for Storm:
Stream processing: Storm can be used to process a stream of new data and update databases in realtime. Unlike the standard approach of doing stream processing with a network of queues and workers, Storm is fault-tolerant and scalable.
Continuous computation: Storm can do a continuous query and stream the results to clients in realtime. An example is streaming trending topics on Twitter into browsers. The browsers will have a realtime view on what the trending topics are as they happen.
Distributed RPC: Storm can be used to parallelize an intense query on the fly. The idea is that your Storm topology is a distributed function that waits for invocation messages. When it receives an invocation, it computes the query and sends back the results. Examples of Distributed RPC are parallelizing search queries or doing set operations on large numbers of large sets."
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