The status quo of data processing is to use MapReduce and processing data from the disk. Although the MapReduce model has taken us far from where we started, often this analysis is latency bound; in other words, the CPU stays idle until data arrives from the disk. In-memory computing provides an alternative to this problem. This white paper introduces in-memory computing and discusses some of the common patterns on how in-memory computing is used.
