{"id":2978,"date":"2012-05-16T07:00:06","date_gmt":"2012-05-16T15:00:06","guid":{"rendered":"http:\/\/www.formtek.com\/blog\/?p=2978"},"modified":"2012-05-16T07:00:06","modified_gmt":"2012-05-16T15:00:06","slug":"storage-architecting-an-hadoop-storage-platform-for-unstructured-data","status":"publish","type":"post","link":"https:\/\/formtek.com\/blog\/storage-architecting-an-hadoop-storage-platform-for-unstructured-data\/","title":{"rendered":"Storage: Architecting an Hadoop Storage Platform for Unstructured Data"},"content":{"rendered":"

The convergence of massive amounts of cheap storage, fast processors, and software algorithms like MapReduce <\/a>are fueling the growth of Big Data technoogy. \u00a0MapReduce is a computing framework that can distribute the processing of a problem described by very large datasets across many computers. \u00a0Hadoop <\/a>is an implementation of the MapReduce Algorithm that combines components of the Google File System<\/a> (GFS) Hadoop’s and makes the software available via the free Apache license.<\/p>\n

Hadoop has spawned a a major part of the Big Data industry. \u00a0A recent CRN article reviews 11 new up-and-coming startups that have built their business plans around Hadoop. \u00a0Hadoop has primarily been viewed as a tool to help in the computing and crunching of massive amounts of data to derive information and analytics.<\/p>\n

Frank Ohlhorst<\/a>,\u00a0Senior Technology Editor at Ziff Davis Enterprise, points out<\/a> that while Hadoop is an enabler of massive data crunching projects, it also can be viewed as an unstructured data storage platform<\/em>. \u00a0Ohlhost wrote that \u00a0“Hadoop solves the most common problem associated with big data: efficiently storing and accessing large amounts of data. \u00a0The intrinsic design of Hadoop allows it to run as a platform that is able to work across a large number of machines that don’t share any memory or disks. With that in mind, it becomes easy to see how Hadoop offers additional value — network managers can simply buy a number of commodity servers, place them in a rack, and run the Hadoop software on each one.”<\/p>\n

Hadoop brings new capabilities that standard centralized storage platforms can’t offer, like “fault-tolerant clustered architecture and the capability to move computing power closer to the data and perform parallel and\/or batch processing of large data sets. It also provides an open ecosystem that supports enterprise architecture layers from data storage to analytics processes.”<\/p>\n

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The convergence of massive amounts of cheap storage, fast processors, and software algorithms like MapReduce are fueling the growth of Big Data technoogy. \u00a0MapReduce is a computing framework that can distribute the processing of a problem described by very large…<\/span><\/p>\n

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