Big Data To Reach $43 Million By 2018, In-Memory Solutions Sought - Page 2
In-Memory Solutions Delivered
Technology designed to handle one or two nodes per millisecond are obsolete. New to big data processing is middleware, the inevitable software which preprocesses for other software in front. Using Java and Scala while driving data through RAM instead of hard disks – traditionally slower – comes GridGain, the potential problem solvers of big data processing. Instead of programmers and businesses only handling two or three hundred nodes for processing, GridGain handles thousands of nodes and terabytes of data in seconds. Companies like Moody’s, Cisco, TomTom and AllConnect, to name some, have begun training and using this in-memory Javascript data processing diatribe.
Hadoop and GridGain do work in synergy, even if preferences are separate. Both have been conceived for parallel processing of big data; both have been adopted by large companies yet Hadoop uses an innovative MapReduce while GridGain uses simplistic compute grids for handling in-memory data. Big data will sink small businesses if unprepared; choose your tool wisely and learn it well.
Follow Technorati