Traditionally, organizations have tried to optimize their business cost on information processing by limiting the information to smaller subsets based on business priority. This was mainly due to the exorbitant cost of storing and processing enterprise data in data stores such as relational databases. Today's technology advancements have reduced the overall cost of data processing through the use of low-cost hardware and open source software. It has also enabled organizations to go beyond smaller data subsets, demanding more data processing capabilities from these systems. Enterprise searches were no exception.

Since enterprise search applications work across multiple applications with different datasets across organizations, it requires lot of data storage and exceptional computation capabilities from the underlying hardware systems. Many organizations optimize cost by preferring to use low-cost distributed systems instead of purchasing high...