Distributed computing is a wide and varied field, but the key distinctions of Hadoop are: (Gandhi, 2012) • Accessible: Hadoop runs on large clusters of machines and/or on cloud computing services such as Amazon’s Elastic Compute Cloud (EC2).• Robust: Because it is designed to run on commodity hardware, Hadoop is constructed with an assumption of frequent hardware malfunctions. It can gracefully handle almost all such failures.• Scalable: Hadoop scales linearly to handle huge data by adding more nodes to the existing cluster.
• Simple: Hadoop also allows users to quickly write efficient parallel code. Hadoop’s accessibility and simplicity have given it an edge over writing and running large distributed programs. Even college students are quickly and cheaply able to create their own Hadoop cluster. On the other hand, its robustness and scalability makes it even more suitable for the most demanding jobs at Yahoo and Facebook. These features make Hadoop popular in both Academics and Industry.