{"id":51830,"date":"2013-11-28T17:41:09","date_gmt":"2013-11-28T14:41:09","guid":{"rendered":"https:\/\/www.altoros.com\/blog\/?p=51830"},"modified":"2023-04-13T05:08:52","modified_gmt":"2023-04-13T02:08:52","slug":"hadoop-benchmark-cloudera-vs-hortonworks-vs-mapr","status":"publish","type":"post","link":"https:\/\/www.altoros.com\/blog\/hadoop-benchmark-cloudera-vs-hortonworks-vs-mapr\/","title":{"rendered":"Hadoop Benchmark: Cloudera vs. Hortonworks vs. MapR"},"content":{"rendered":"<div id=\"ez-toc-container\" class=\"ez-toc-v2_0_79_2 counter-hierarchy ez-toc-counter ez-toc-transparent ez-toc-container-direction\">\n<div class=\"ez-toc-title-container\">\n<p class=\"ez-toc-title\" style=\"cursor:inherit\">Table of Contents<\/p>\n<span class=\"ez-toc-title-toggle\"><a href=\"#\" class=\"ez-toc-pull-right ez-toc-btn ez-toc-btn-xs ez-toc-btn-default ez-toc-toggle\" aria-label=\"Toggle Table of Content\"><span class=\"ez-toc-js-icon-con\"><span class=\"\"><span class=\"eztoc-hide\" style=\"display:none;\">Toggle<\/span><span class=\"ez-toc-icon-toggle-span\"><svg style=\"fill: #999;color:#999\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" class=\"list-377408\" width=\"20px\" height=\"20px\" viewBox=\"0 0 24 24\" fill=\"none\"><path d=\"M6 6H4v2h2V6zm14 0H8v2h12V6zM4 11h2v2H4v-2zm16 0H8v2h12v-2zM4 16h2v2H4v-2zm16 0H8v2h12v-2z\" fill=\"currentColor\"><\/path><\/svg><svg style=\"fill: #999;color:#999\" class=\"arrow-unsorted-368013\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"10px\" height=\"10px\" viewBox=\"0 0 24 24\" version=\"1.2\" baseProfile=\"tiny\"><path d=\"M18.2 9.3l-6.2-6.3-6.2 6.3c-.2.2-.3.4-.3.7s.1.5.3.7c.2.2.4.3.7.3h11c.3 0 .5-.1.7-.3.2-.2.3-.5.3-.7s-.1-.5-.3-.7zM5.8 14.7l6.2 6.3 6.2-6.3c.2-.2.3-.5.3-.7s-.1-.5-.3-.7c-.2-.2-.4-.3-.7-.3h-11c-.3 0-.5.1-.7.3-.2.2-.3.5-.3.7s.1.5.3.7z\"\/><\/svg><\/span><\/span><\/span><\/a><\/span><\/div>\n<nav><ul class='ez-toc-list ez-toc-list-level-1 ' ><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-1\" href=\"https:\/\/www.altoros.com\/blog\/hadoop-benchmark-cloudera-vs-hortonworks-vs-mapr\/#Evaluating_Hadoop_distributions_across_7_workloads\" >Evaluating Hadoop distributions across 7 workloads<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-2\" href=\"https:\/\/www.altoros.com\/blog\/hadoop-benchmark-cloudera-vs-hortonworks-vs-mapr\/#Hadoop_performance_bigger_doesnt_mean_faster\" >Hadoop performance: bigger doesn&#8217;t mean faster<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-3\" href=\"https:\/\/www.altoros.com\/blog\/hadoop-benchmark-cloudera-vs-hortonworks-vs-mapr\/#Further_reading\" >Further reading<\/a><\/li><\/ul><\/nav><\/div>\n<h3><span class=\"ez-toc-section\" id=\"Evaluating_Hadoop_distributions_across_7_workloads\"><\/span>Evaluating Hadoop distributions across 7 workloads<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p><b>Cloudera<\/b>, <b>Hortonworks<\/b>, and <b>MapR<\/b> are the most popular Hadoop distributions available today. However, even with this short list, there are few unbiased comparisons of their cluster performance. So, today we are introducing a 65-page <a href=\"https:\/\/www.altoros.com\/research-papers\/hadoop-distributions-cloudera-vs-hortonworks-vs-mapr\/\">research paper<\/a> that contains a vendor-independent overview of Cloudera, Hortonworks, and MapR distributions.<\/p>\n<p><center><a href=\"https:\/\/www.altoros.com\/blog\/wp-content\/uploads\/2013\/11\/hadoop-frameworks-benchmark-altoros.jpg\"><img loading=\"lazy\" decoding=\"async\" width=\"400\" height=\"60\" src=\"https:\/\/www.altoros.com\/blog\/wp-content\/uploads\/2013\/11\/hadoop-frameworks-benchmark-altoros.jpg\" class=\"aligncenter size-full wp-image-54427\" \/><\/a><\/center><\/p>\n<p><a href=\"https:\/\/www.altoros.com\/blog\/author\/vladimir-starostenkov\/\">Vladimir Starostenkov<\/a> of Altoros compared the throughput of 8-, 12-, and 16-node clusters against the performance of a 4-node cluster. (The speed values of data processing on 8-, 12-, and 16-node clusters were divided by the throughput of a 4-node cluster.)\u00a0The results were quite unexpected.<\/p>\n<p>&nbsp;<\/p>\n<h3><span class=\"ez-toc-section\" id=\"Hadoop_performance_bigger_doesnt_mean_faster\"><\/span>Hadoop performance: bigger doesn&#8217;t mean faster<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>In a recent <a href=\"https:\/\/www.techtarget.com\/searchdatamanagement\/feature\/Big-data-fast-Avoiding-Hadoop-performance-bottlenecks\" target=\"_blank\" rel=\"noopener noreferrer\">interview<\/a> to TechTarget, our R&amp;D Engineer <a href=\"https:\/\/www.linkedin.com\/in\/dmitriy-kalyada-648aa538\/\" rel=\"noopener\" target=\"_blank\">Dmitriy Kalyada<\/a> explained why adding nodes to a Hadoop cluster not always results in better performance. The new benchmark of Hadoop distributions confirms this behavior under several workloads.<\/p>\n<p style=\"text-align: left;\">For instance, when sorting unstructured text data (the Sort workload), the performance of a MapR cluster was growing linearly (as we were increasing its size from 4 to 8 nodes). After that, when new machines\u00a0were added, the throughput of each separate node was degrading.<\/p>\n<p><center><a href=\"https:\/\/www.altoros.com\/blog\/wp-content\/uploads\/2013\/11\/mapr_performance.png\"><img decoding=\"async\" src=\"https:\/\/www.altoros.com\/blog\/wp-content\/uploads\/2013\/11\/mapr_performance.png\" alt=\"\" width=\"640\" class=\"alignnone size-full wp-image-51835\" \/><\/a><small>The MapR cluster performance<\/small><\/center><\/p>\n<p style=\"text-align: left;\">As you can see on the diagram, an 8-node cluster turned out to be faster than clusters of 12 and 16 nodes. The same situation was observed in the DFSIO write test. Other Hadoop distributions had similar results under some of the workloads, too.<\/p>\n<p>Download the <a href=\"https:\/\/www.altoros.com\/research-papers\/hadoop-distributions-cloudera-vs-hortonworks-vs-mapr\/\">benchmark<\/a> to see all the performance results (83 diagrams, 7 types of workloads), including:<\/p>\n<ul>\n<li>detailed performance results for 4-, 8-, 12-, and 16-node\u00a0clusters<\/li>\n<li>how the size of a cluster affects data processing speed<\/li>\n<li>what issues slow down deployment and how to maximize Hadoop processing speed<\/li>\n<li>how different clusters behave under CPU and disk-bound workloads (including Bayes, DFSIO, Hive aggregation, PageRank, Sort, TeraSort, and WordCount)<\/li>\n<\/ul>\n<p style=\"margin-top:16px;\">In the comments below, let us know what you think about the performance results.<\/p>\n<p>&nbsp;<\/p>\n<h3><span class=\"ez-toc-section\" id=\"Further_reading\"><\/span>Further reading<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<ul>\n<li><a href=\"https:\/\/www.altoros.com\/blog\/building-stock-trading-strategies-20-faster-with-hadoop\/\">Building Stock Trading Strategies: 20% Faster with Hadoop<\/a><\/li>\n<li><a href=\"https:\/\/www.altoros.com\/research-papers\/hadoop-gpu-boost-performance-of-your-big-data-project-by-50x-200x-2\/\">Hadoop + GPU: Boost Performance of Your Big Data Project by 50x-200x?<\/a><\/li>\n<li><a href=\"https:\/\/www.altoros.com\/research-papers\/hadoop-based-movie-recommendation-engine-a-comparison-of-the-apriori-algorithm-vs-the-k-means-method\/\">Hadoop-based Movie Recommendation Engine: A Comparison of the Apriori Algorithm vs. the k-means Method<\/a><\/li>\n<\/ul>\n","protected":false},"excerpt":{"rendered":"<p>Evaluating Hadoop distributions across 7 workloads<\/p>\n<p>Cloudera, Hortonworks, and MapR are the most popular Hadoop distributions available today. However, even with this short list, there are few unbiased comparisons of their cluster performance. So, today we are introducing a 65-page research paper that contains a vendor-independent overview of Cloudera, Hortonworks, and [&#8230;]<\/p>\n","protected":false},"author":5,"featured_media":54428,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"content-type":"","footnotes":"","_links_to":"","_links_to_target":""},"categories":[7],"tags":[894,895],"class_list":["post-51830","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-news-and-opinion","tag-benchmarking","tag-research-and-development"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v26.6 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Hadoop Benchmark: Cloudera vs. Hortonworks vs. MapR | Altoros<\/title>\n<meta name=\"description\" content=\"Our new study demonstrates the performance results of the major Hadoop distributions operating under seven types of workloads.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.altoros.com\/blog\/hadoop-benchmark-cloudera-vs-hortonworks-vs-mapr\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Hadoop Benchmark: Cloudera vs. Hortonworks vs. MapR | Altoros\" \/>\n<meta property=\"og:description\" content=\"Evaluating Hadoop distributions across 7 workloads Cloudera, Hortonworks, and MapR are the most popular Hadoop distributions available today. 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