Big Data Electronic Health Records Data Management and Analysis on Cloud with MongoDB: A NoSQL Database

The emergence of cloud computing architecture allows huge computations to run inexpensively and efficiently. Big Data systems like Hadoop are designed to run on commodity hardware and can process huge data of any data types. This makes operational Big Data workloads much easier to manage, cheaper and faster to implement. Traditional relational databases cannot scale horizontally when the data grows. A new database architecture which can handle the structured and unstructured data like NoSQL databases are designed for cloud computing environment to handle such data. NoSQL databases are natively able to handle load by spreading data among many servers, making them a natural fit for the cloud computing environment. The document data model used in NoSQL databases like MongoDB makes it natural fit for cloud computing environment. MongoDB is a database which is built specially for the cloud because it supports scale out architecture. In this paper we study how big data Electronic Health Records (EHR) systems data management and analysis on cloud can be achieved using MongoDB. We also compare how this NoSQL database performs well than SQL based EHR systems. Keywords—BigData; NoSQL; Cloud computing; EHR