Due to the emergence of internet and the futuristic internet of things the data is enhancing day by day. It is not only difficult to stock the data in proper manner but also provide security and authentication to it. The huge amount of data is produced form applications like internet, social networks, bio-informatics, sensors, weather forecasting etc. Processing if this gigantic amount of data using database system is impossible. The voluminous of data, challenges the research scholars for preventing the cyber criminals for doing their business.There is no hard and fast rule about precisely what size a database needs to be in order for the data inside of it to be considered "big." [12] Instead, what typically defines big data is the need for new techniques and tools in order to be able to process it[12]. In order to use big data, we need programs which span multiple physical and/or virtual machines working together in concert in order to process all of the data in a reasonable span of time. Getting programs on multiple machines to work together in an efficient way, so that each program knows which components of the data to process, and then being able to put the results from all of the machines together to make sense of a large pool of data takes special programming techniques[12]. Since it is typically much faster for programs to access data stored locally instead of over a network, the distribution of data across a cluster and how those machines are networked together are also important considerations which must be made when thinking about big data problems [12]. Nobody will disagree that the existing world is going through the big Data cohort [10].