Why the Fast Data World Needs a Proven and Mature In-Memory Data Fabric
Much of what human beings experience as commonplace today – social networking, online gaming, mobile and wearable computing — was impossible a decade ago. One thing is certain: we’re going to see even more impressive advances in the next few years. However, this will be the result of a fundamental change in computing, as current methods have reached their limit in terms of speed and volume.
Traditional disk-based storage infrastructure is far too slow to meet today’s data demands for speed at volume, which are growing exponentially. In-memory computing (IMC) offers the only practical way to scale to today’s computing demands. Although IMC may once have been the domain of only the most well-funded organizations, the falling cost of RAM means that it can now be accomplished by any organization on commodity hardware.
GridGain has been at the cutting edge of developing a comprehensive in-memory data processing framework for real-time transactional and analytical use cases for many years. Hundreds of organizations around the globe now use its proven open source technology under the Apache 2.0 license. This work has culminated in the recent release of its application- and data-agnostic GridGain In-Memory Data Fabric. GridGain’s in-memory data fabric code base shares the goals of easy accessibility and free redistribution with other memory-centric, open source data exchange frameworks that have emerged — most notably the Apache Spark project in the Hadoop world.
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