Three Big Problems Big Data Will Create in 2014
When it comes to application performance, IT organizations have been engaged in a multi-decade arms race to gain a competitive edge over rivals. With the rise of in-memory computing, that arms race is moving into another phase.
One of the players fueling that arms race is ScaleOut Software, which just released an update to its in-memory data grid software that adds support for C++ and versions of its ScaleOut hServer for Hadoop and ScaleOut GeoServer grid management software. The software can now be deployed both on-premise and in the Amazon Web Services (AWS) cloud. In addition, ScaleOut Software announced support for an implementation of ScaleOut hServer for Hadoop that now runs on Windows.
ScaleOut Software CEO Bill Bain says the thing that distinguishes ScaleOut StateServer most is that it’s built around a scale-out architecture that makes it simpler for IT organizations to add additional processing power as needed. The scale-out architecture, adds Bain, is what also makes it possible to deploy Hadoop on top of ScaleOut in a way that takes advantage of the inherent parallelism of the platform to dramatically improve the performance of applications invoking MapReduce or an alternative Hadoop interface that ScaleOut Software developed.
In addition to open source C++ application programming interfaces (APIs), ScaleOut Software already supports Java APIs. Bain says C++ support for an in-memory data grid architecture required some additional engineering effort to take advantage of parallelism that ScaleOut Software is now making available as open source code. Bain says that the company’s strategy is to open source APIs as part of an effort to increase the base of developers creating applications for its in-memory data grid platform.
ScaleOut Software is hardly the only vendor bringing an in-memory database grid to market. But because it can handle multiple petabytes of data in a way that scales out over time, ScaleOut Software is betting that as familiarity with Big Data applications matures, more IT organizations are going to be looking for innovative ways to deploy those applications to take full advantage of in-memory computing architecture.
