  MapReduce is a technique used to vastly improve distributed processing of
data and can massively speed up computation. Hadoop and its MapReduce relies on
JVM and Java which is expensive on memory. High Performance Computing based
MapReduce framework could be used that can perform more memory-efficiently and
faster than the standard MapReduce. This paper explores an entirely C++ based
approach to the MapReduce and its feasibility on multiple factors like
developer friendliness, deployment interface, efficiency and scalability. This
paper also introduces Delayed Reduction and deployment techniques that can
speed up MapReduce in a compiled environment.
