Apache Storm – Introduction

  • Apache Storm is a distributed real-time big data-processing system.
  • Storm is designed to process vast amount of data in a fault-tolerant and horizontal scalable method.
  • It is a streaming data framework that has the capability of highest ingestion rates.
  • Though Storm is stateless, it manages distributed environment and cluster state via Apache Zookeeper.
  • It is simple and you can execute all kinds of manipulations on real-time data in parallel.
  • Apache Storm is continuing to be a leader in real-time data analytics.

Storm is easy to setup, operate and it guarantees that every message will be processed through the topology at least once.

  • Basically Hadoop and Storm frameworks are used for analysing big data.
  • Both of them complement each other and differ in some aspects.
  • Apache Storm does all the operations except persistency, while Hadoop is good at everything but lags in real-time computation.
  • The following table compares the attributes of Storm and Hadoop.
Storm Hadoop
Real-time stream processing Batch processing
Stateless Stateful
Master/Slave architecture with ZooKeeper based coordination. The master node is called as nimbus and slaves are supervisors. Master-slave architecture with/without ZooKeeper based coordination. Master node is job tracker and slave node is task tracker.
A Storm streaming process can access tens of thousands messages per second on cluster. Hadoop Distributed File System (HDFS) uses MapReduce framework to process vast amount of data that takes minutes or hours.
Storm topology runs until shutdown by the user or an unexpected unrecoverable failure. MapReduce jobs are executed in a sequential order and completed eventually.
Both are distributed and fault-tolerant
If nimbus / supervisor dies, restarting makes it continue from where it stopped, hence nothing gets affected. If the JobTracker dies, all the running jobs are lost.


Apache Storm Benefits

Here is a list of the benefits that Apache Storm offers −

  • Storm is open source, robust, and user friendly. It could be utilized in small companies as well as large corporations.
  • Storm is fault tolerant, flexible, reliable, and supports any programming language.
  • Allows real-time stream processing.
  • Storm is unbelievably fast because it has enormous power of processing the data.
  • Storm can keep up the performance even under increasing load by adding resources linearly. It is highly scalable.
  • Storm performs data refresh and end-to-end delivery response in seconds or minutes depends upon the problem. It has very low latency.
  • Storm has operational intelligence.
  • Storm provides guaranteed data processing even if any of the connected nodes in the cluster die or messages are lost.


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