Apache Storm is a scalable, fault-tolerant, distributed, real-time computation system. Storm makes it easy to reliably process streams of data. Storm has many use cases: real-time analytics, online machine learning, continuous computation, ETL, and others. Storm can process over 1 million tuples per second per node. The following are the key features of Storm:
Real-time computation
Guarantees data will be processed
Scalable
Fault tolerant
Hadoop and MapReduce provide a great batch processing capability. HBase provides the low latency store. Storm provides low latency transformation so that real-time processing can be performed on the raw data.
Let's consider our airline on-time performance use case. In the previous chapters, we saw how to ingest, transform, and analyze historical data using batch processing. With Storm, we can now process real-time feeds and analyze both historical...