From the ACM, viewed yesterday, technical, note its application to the IOT, which will produce lots of fast data. This all gets fast, and thus interesting above 100K messages per second. The first four chapters of the free e-Book linked to below are a nice, non-technical intro to the concept and values of fast data.
The Fast Data Challenge and Picking the Right Database: Why One Size Doesn’t Fit All
Interacting with fast data, data that is in motion, is a fundamentally different process than interacting with big data that is at rest. And few businesses have the ability to extract the value of that data when it matters most — at the moment it arrives — because traditional database technology simply hasn't kept pace.
Dr. Michael Stonebraker, Professor at MIT and co-founder of VoltDB, has long held the belief that, without the right database architecture in place, today's organizations run the risk of being left behind in a world that's smarter and faster than what legacy systems can handle.
It’s time to rethink the technology stack needed to enable fast data applications. What’s needed is a framework for making technology choices and architecting fast data applications, the fast data stack. The fast data stack has three levels: data ingestion, real-time analytics and decisions, and data export. ....
You may have to register for this. View here, I understand this will be present until May 2016. All Seminar Slides.
And a free background e-Book. About the open source VoltDB system.
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