How to reconcile Real-Time and Batch processing using In-Memory technology

by Fabien Sanglier in

As you might remember, we(*) participated in a “Plugfest”(**) earlier this year in San Diego. Here is the summary post of what we built for that occasion:

This time around, we entered the plugfest competition as a technology provider at the AFCEA Cyber Symposium, which happened last week (June 25-27 2013) in Baltimore. We not only provided technologies components and data feeds to the challengers (San Diego State University, GMU, Army PEO C3T milSuite), but also built a very cool Fraud Detection and Money Laundering demo which was 1 of the plugfest use case for this cyber event.

Our demo was centered around a fundamental “Big Data” question: How can you detect fraud on 100,000s transactions per seconds in real-time (which is absolutely critical if you don’t want to lose lots of $$$$ to fraud) while efficiently incorporating in that real-time process data from external systems (i.e. data warehouse or hadoop clusters).
Or in more general words: How to reconcile Real-time processing and Batch processing when dealing with large amounts of data.


Check out his solution here

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