In this blog, Nikita Ivanov attempts to update the definition of in-memory computing and the value it provides. Clearly his point is that in-memory computing is heading to the mainstream.

He says, “Last year GridGain won an open tender for one of the largest banks in the world. The tender was for a risk analytics system to provide real-time analysis of risk for the bank’s trading desk (common use case for in-memory computing in the financial industry). In this tender GridGain software demonstrated one billion (!) business transactions per second on 10 commodity servers with the total of 1TB of RAM. The total cost of these 10 commodity servers? Less than $25K.

Now, read the previous paragraph again: one billion financial transactions per second on $25K worth of hardware. That is the in-memory computing difference — not just 2-3x times faster; more than 100x faster than theoretically possible even with the most expensive flash-based storage available on today’s market (forget about spinning disks). And 1TB of flash-based storage alone would cost 10x of entire hardware setup mentioned.”