Software AG Makes Case for Real-Time Middleware

Mike Vizard

No matter where you turn these days, everybody wants to be able to share data in real time. Whether it is a financial services transaction or mobile computing application, the real-time requirement has become the same.

The good news is that the shift toward real-time computing gives IT organizations an interesting opportunity to start rationalizing some of their middleware stacks. Recognizing that general trend, Software AG has begun delivering via its Terracotta subsidiary and as part of the webMethods product line a real-time data streaming middleware platform that incorporates elements of the middleware technology that Software AG gained with the acquisition of webMethods in 2007 and my-Channels earlier this year.

According to Eddie McDaid, managing director for Universal Messaging at Terracotta, with the rise of in-memory computing, it’s almost inevitable that the majority of enterprise applications will soon be processing data in real time. McDaid says that fundamental shift in enterprise computing will require a Universal Messaging middleware framework capable of providing the processing speed at scale that will be required to keep pace with those applications.

That shift, adds McDaid, also creates the opportunity for IT organizations to finally leverage a common set of application programming interfaces in a world where software-oriented architecture (SOA) is converging with other integration approaches such as RESTful APIs.

It’ll take years for most IT organizations to make the shift toward in-memory computing. But Software AG is making the case that the first applications that will make that shift will be among the organization’s most mission-critical, which tend to have the greatest need for maximum amount of performance.

Whatever the ultimate decision, a middleware era that was defined by batch processing of application data is coming to a close. The end result is a need for new architecture for keeping up with events as they actually happen, no matter how much data is involved.

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