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Difference Between Apache Hadoop and Apache Storm
  • Last Updated : 06 May, 2020

Apache Hadoop: It is a collection of open-source software utilities that facilitate using a network of many computers to solve problems involving massive amounts of data and computation. It provides a software framework for distributed storage and processing of big data using the MapReduce programming model.

Apache Storm: It is a distributed stream processing computation framework written predominantly in the Clojure programming language. Originally created by Nathan Marz and the team at BackType, the project was open-sourced after being acquired by Twitter.

Apache-Hadoop-vs-Apache-Storm

Below is a table of differences between Apache Hadoop and Apache Storm:

FeaturesApache HadoopApache Storm
ProcessingDistributed batch processing which uses MapReduceDistributed real-time data processing which uses DAGs
LatencyHigh Latency i.e slow computationLow Latency i.e fast computation
Written LanguageWhole frame work is written in JavaFrame work is written in Clojure and Java
Streaming processingIt is State-ful streaming processingIt is State-less streaming processing
SetupEasy to setup but operating cluster is hardEasy to use
Data streamingData is dynamic and continuously streamedData is static and nonvolatile i.e data is persistence
SpeedSlowFast
Use casesIt is used in Twitter, Navisite, Wego etcIt is used in Black Box Data, Search Engine Data etc

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