{"id":12085,"date":"2014-12-27T23:00:00","date_gmt":"2014-12-27T23:00:00","guid":{"rendered":"http:\/\/cloudcomputing.sys-con.com\/node\/2869983"},"modified":"2014-12-27T23:00:00","modified_gmt":"2014-12-27T23:00:00","slug":"hadoop-100x-faster-by-gridgain-cloudexpo-bigdata","status":"publish","type":"post","link":"https:\/\/icloud.pe\/blog\/hadoop-100x-faster-by-gridgain-cloudexpo-bigdata\/","title":{"rendered":"Hadoop \u2013 100x Faster By @GridGain | @CloudExpo [#BigData]"},"content":{"rendered":"<p>It is almost two years ago now when Dmitriy and I stood in front of the white board at the old GridGain office thinking: \u201cHow can we deliver all the real-time performance of GridGain\u2019s in-memory technology to Hadoop customers without asking them rip and replace their systems and without asking them to move their datasets off Hadoop?\u201d.<br \/>\nIf you know anything about Hadoop architecture &#8211; the task seemed daunting to us and it proved to be one of the most challenging engineering feat that we have accomplished so far.<br \/>\nAfter almost 24 months of development, tens of thousands of lines of Java, Scala and C++ code, multiple design iterations, several releases and dozens of benchmarks later we have the product that can deliver real-time performance to Hadoop with only minimal integration and no ETL required. Backed-up by customer deployments that prove our performance claims and validate our architecture<\/p>\n<p><a href=\"http:\/\/cloudcomputing.sys-con.com\/node\/2869983\" >read more<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>It is almost two years ago now when Dmitriy and I stood in front of the white board at the old GridGain office thinking: &ldquo;How can we deliver all the real-time performance of GridGain&rsquo;s in-memory technology to Hadoop customers without asking them rip and replace their systems and without asking them to move their datasets off Hadoop?&rdquo;.<br \/>\nIf you know anything about Hadoop architecture &#8211; the task seemed daunting to us and it proved to be one of the most challenging engineering feat that we have accomplished so far.<br \/>\nAfter almost 24 months of development, tens of thousands of lines of Java, Scala and C++ code, multiple design iterations, several releases and dozens of benchmarks later we have the product that can deliver real-time performance to Hadoop with only minimal integration and no ETL required. Backed-up by customer deployments that prove our performance claims and validate our architecture<\/p>\n<p><a href=\"http:\/\/cloudcomputing.sys-con.com\/node\/2869983\" target=\"_blank\">read more<\/a><\/p>\n","protected":false},"author":3,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[],"tags":[],"class_list":["post-12085","post","type-post","status-publish","format-standard","hentry"],"_links":{"self":[{"href":"https:\/\/icloud.pe\/blog\/wp-json\/wp\/v2\/posts\/12085","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/icloud.pe\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/icloud.pe\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/icloud.pe\/blog\/wp-json\/wp\/v2\/users\/3"}],"replies":[{"embeddable":true,"href":"https:\/\/icloud.pe\/blog\/wp-json\/wp\/v2\/comments?post=12085"}],"version-history":[{"count":0,"href":"https:\/\/icloud.pe\/blog\/wp-json\/wp\/v2\/posts\/12085\/revisions"}],"wp:attachment":[{"href":"https:\/\/icloud.pe\/blog\/wp-json\/wp\/v2\/media?parent=12085"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/icloud.pe\/blog\/wp-json\/wp\/v2\/categories?post=12085"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/icloud.pe\/blog\/wp-json\/wp\/v2\/tags?post=12085"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}