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Dealing with big data: The storage implications
This article is part of the Storage magazine issue of Vol. 11 Num. 3 May 2012
Whether it’s defining “big data,” understanding Hadoop or assessing the impact of large data stores, storage pros need a clear understanding of the big data trend. It seems impossible to get away from the term “big data” nowadays. The challenge is that the industry lacks a standard definition for what big data is. Enterprise Strategy Group (ESG) defines big data as “data sets that exceed the boundaries and sizes of normal processing capabilities, forcing you to take a non-traditional approach.” We apply the term “big data” to any data set that breaks the boundaries and conventional capabilities of IT designed to support day-to-day operations. @pb These boundaries can be encountered on multiple fronts: The transaction volume can be so high that traditional data storage systems hit bottlenecks and can’t complete operations in a timely manner. They simply don’t have enough processing horsepower to handle the volume of I/O requests. Sometimes they don’t have enough spindles in the environment to handle all the I/O requests. This ...
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