Storm can process streaming data really fast (clocked at over one million messages per second per node); it is scalable (thousands of worker nodes of cluster), fault tolerant, and reliable (message processing is guaranteed). Storm is easy to use and deploy, which also eases its maintainability. Hadoop is primarily designed for batch processing and for Lambda Architecture systems. Storm is well-integrated with Hadoop, in order to provide distributed real-time streaming analysis reliably with good fault tolerance for big data.
Storm was developed by Twitter and later contributed to Apache. Storm's benchmark results are quite outstanding at over a million sets of data called tuples processed per second per node. Storm utilizes a Thrift interface; hence, the client can be written in any language and even non-JVM language communicates over JSON-based protocol. Considering the complexity of Storm, it is a fairly easy-to-use API.