Hadoop is a system that allows the circulated preparation of huge datasets across bunches of PCs utilizing basic programming models. It was inspired by a specialized document published by Google. The word Hadoop doesn’t have any significance. Doug Cutting, who found Hadoop, named it after his child’s yellow-shaded toy elephant.

The four key qualities of Hadoop are that it is practical, its systems are exceptionally affordable as common PCs can be utilized for data preparing. It is dependable as it stores duplicates of the data on various machines and is impervious to equipment disappointment. It is effectively adaptable both, on a level plane, and vertically. A couple of additional hubs help in scaling up the structure. It is adaptable and you can store as much organized and unstructured data as you have to and choose to utilize them later.

Current systems get terabytes of data every day, and it is hard for the conventional PCs or Relational Database Management System (RDBMS) to push high volumes of data to the processor. Hadoop brought an extreme methodology. In Hadoop, the program goes to the data, not the other way around. It at first appropriates the data to numerous systems and later runs the calculation any place the data is found.