Sourav Mazumder, Infosys
Matching data coming from multiple external and internal sources is challenge for any IT organization across industry verticals like Retail, Manufacturing, Banking, etc. The problem statement is becoming more and more daunting given recent trends of B2B, B2C, B2P business ecosystem using loosely coupled business interfaces of SoA where agility and flexibility are keys. In the proposed presentation we would take a look on how MongoDB's document based schema is a natural fit to build a robust Data Matching Engine addressing this business challenge and how MongoDB's MapReduce feature provides the necessary scale of tackling large volume Data Matching load. We'll also touch upon on the scalability metrics which can be achieved using MongoDB's distributed computing features like sharding, replica sets, delayed replication etc.