{"id":23317,"date":"2018-07-28T09:18:53","date_gmt":"2018-07-28T09:18:53","guid":{"rendered":"https:\/\/data-flair.training\/blogs\/?p=23317"},"modified":"2018-07-28T09:18:53","modified_gmt":"2018-07-28T09:18:53","slug":"kafka-vs-storm","status":"publish","type":"post","link":"https:\/\/data-flair.training\/blogs\/kafka-vs-storm\/","title":{"rendered":"Kafka vs Storm: Feature Wise Comparison of Kafka & Storm"},"content":{"rendered":"

Today, in this article, \u201cApache Kafka vs Storm: Difference Between Storm and Kafka\u201d we will see the complete comparison for both Kafka and Storm. So, let\u2019s start with the brief introduction of Kafka<\/strong> and Storm to understand the comparison well.<\/span><\/p>\n

Comparison of Kafka Vs Storm<\/span><\/h2>\n

i. What is Kafka<\/span><\/h3>\n

In order to enable communication between Kafka Producers<\/strong> and Kafka Consumers<\/strong> using message-based topics, we use Apache Kafka. It is very fast, scalable and fault-tolerant, publish-subscribe messaging system. <\/span><\/p>\n

Kafka plays the role of a platform for high-end new generation distributed applications. Moreover, it permits a huge number of permanent or ad-hoc consumers. As a benefit, Kafka is highly resilient to node failures and also offers automatic recovery. <\/span><\/p>\n

Hence we can say Kafka is the best choice for communication and integration between components of large-scale data system because of this special feature.<\/span><\/p>\n

ii. What is Storm?<\/span><\/h3>\n

An open source, distributed, reliable, and fault-tolerant system, is Apache Storm. It has several uses, for example, the Extract Transformation Load (ETL) paradigm, real-time analytics, online machine learning, and continuous computation.<\/span><\/p>\n

It has various components that work together for the purpose of streaming as well as data processing such as Spout and Bolt. On defining both:<\/span><\/p>\n

    \n
  • Spout<\/span><\/li>\n<\/ul>\n

    A source of the stream is what we call Spout.<\/span><\/p>\n

      \n
    • Bolt<\/span><\/li>\n<\/ul>\n

      Whereas, Bolt is a component to which, spout passes the data.<\/span>
      \nNow, let’s start the featurewise Comparison of Kafka Vs Storm.<\/p>\n

      Apache Kafka vs Storm<\/span><\/h2>\n

      Here are some Key Differences Between Apache Kafka vs Storm:<\/span><\/p>\n

      a. Data Security<\/span><\/h3>\n

      i.\u00a0Apache Kafka<\/strong>
      \nBasically, Kafka does not guarantee data loss, or we can say it have the very low guarantee. For Example, for 7 Million message transactions per day, Netflix achieved 0.01% of data loss.<\/span><\/p>\n

      ii. Apache Storm<\/strong>
      \nOn comparison with Kafka, Storm guarantees full data security. <\/span><\/p>\n

      b. Data Storage<\/span><\/h3>\n

      i.\u00a0Apache Kafka<\/strong>
      \nApache Kafka store its data on the local filesystem, such as EXT4 and XFS.<\/span>
      \nii. Apache Storm<\/strong>
      \nOn the other hand, Storm is just a data processing framework. That says it doesn’t store data it just transfers it from input to Output stream. <\/span><\/p>\n

      c. Real-time messaging system<\/span><\/h3>\n

      i.\u00a0Apache Kafka<\/strong>
      \nBefore processing only, Kafka used to store incoming messages.<\/span><\/p>\n

      ii. Apache Storm<\/strong>
      \nHowever, Storm works on a Real-time messaging system.<\/span><\/p>\n

      d. Processing\/ Transforming<\/span><\/h3>\n

      i.\u00a0Apache Kafka<\/strong>
      \nWe use Apache Kafka for processing the real-time data.<\/span>
      \nii. Apache Storm<\/strong>
      \nWhereas, we use Storm for transforming the data.<\/span><\/p>\n

      e. Data Source<\/span><\/h3>\n

      i.\u00a0Apache Kafka<\/strong>
      \nBasically, Kafka pulls the data from the actual source of data.<\/span>
      \nii. Apache Storm<\/strong>
      \nOn the other hand, Storm gets the data from Kafka itself regarding further processes.<\/span><\/p>\n

      f. Basic Task<\/span><\/h3>\n

      i.\u00a0Apache Kafka<\/strong>
      \nWhile it comes to transferring real-time application data from the source application<\/strong> to another, we use Kafka application.<\/span>
      \nii. Apache Storm<\/strong>
      \nWell, we use Storm for aggregation as well as computation purpose.<\/span><\/p>\n

      g. Zookeeper Dependency<\/span><\/h3>\n

      i.\u00a0Apache Kafka<\/strong>
      \nWhile setting up the Kafka, it\u2019s mandatory to have Apache Zookeeper<\/strong>.<\/span><\/p>\n

      ii. Apache Storm<\/strong>
      \nWhereas, we don\u2019t need Zookeeper to make Storm work.<\/span><\/p>\n

      h. Fault-Tolerant<\/span><\/h3>\n

      i.\u00a0Apache Kafka<\/strong>
      \nDue to Zookeeper, Kafka is fault tolerant.<\/span>
      \nii. Apache Storm<\/strong>
      \nThe storm is capable of auto-restart its daemons itself.<\/span><\/p>\n

      i. Inventor<\/span><\/h3>\n

      i.\u00a0Apache Kafka<\/strong>
      \nKafka is invented by LinkedIn<\/strong>.<\/span>
      \nii. Apache Storm<\/strong>
      \nWhereas, Twitter<\/strong> invented Apache Storm.<\/span><\/p>\n

      j. Language Support<\/span><\/h3>\n

      i.\u00a0Apache Kafka<\/strong>
      \nBasically, Kafka can work with all languages but while it comes to work best, Kafka works best with Java language only.<\/span>
      \nii. Apache Storm<\/strong>
      \nStrom supports all the languages.<\/span><\/p>\n

      k. Latency<\/span><\/h3>\n

      i.\u00a0Apache Kafka<\/strong>
      \nKafka\u2019s Latency depends upon Data Source, which is generally less than 1-2 seconds.<\/span>
      \nii. Apache Storm<\/strong>
      \nWhile it comes to latency, it is Millisecond latency.<\/span><\/p>\n

      l. Stream processing<\/span><\/h3>\n

      i.\u00a0Apache Kafka<\/strong>
      \nKafka performs Small-Batch Processing.<\/span><\/p>\n

      ii. Apache Storm<\/strong>
      \nWhile Storm Performs Micro-Batch Processing.<\/span>
      \nSo, this was all in Kafka vs Storm. Hope you like our explanation.<\/p>\n

      Conclusion: Apache Kafka vs Storm<\/span><\/h2>\n

      Hence, we have seen that both Apache Kafka and Storm are independent of each other and also both have some different functions in Hadoop<\/strong> cluster environment. <\/span><\/p>\n

      Apart from all, we can say Apache both are great for performing real-time analytics and also both have great capability in the real-time streaming. Still, if any doubt regarding Kafka vs Storm, ask in the comment tab.<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"

      Today, in this article, \u201cApache Kafka vs Storm: Difference Between Storm and Kafka\u201d we will see the complete comparison for both Kafka and Storm. So, let\u2019s start with the brief introduction of Kafka and...<\/p>\n","protected":false},"author":5,"featured_media":23368,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[9],"tags":[2773,3868,7973,13876,15798,15991],"class_list":["post-23317","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-kafka","tag-comparison-of-kafka-and-storm","tag-difference-between-kafka-and-storm","tag-kafka-vs-storm","tag-storm-vs-kfaka","tag-what-is-kafka","tag-what-is-storm"],"yoast_head":"\nKafka vs Storm: Feature Wise Comparison of Kafka & Storm - DataFlair<\/title>\n<meta name=\"description\" content=\"Kafka vs Storm,what is Kafka,what is Storm,Difference between Kafka and storm,feature wise comparison of Apache Kafka and Storm\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/data-flair.training\/blogs\/kafka-vs-storm\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Kafka vs Storm: Feature Wise Comparison of Kafka & Storm - 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