Abstract:

Humanity produces gigantic amounts er data every day. By 2020, the amount of information we want to store to keep them will be around 44 trillion gigabytes. So far, however, our traditional databases are limited in the storage and processing oi this large and complex data and we do not have a reliable physical storage medium that can Withstand the weather, The most obvious solution is of course to multiply storage units, This general principle is not valid for large data and its realization does not flow from source. So, With the advent er Big Data, a new set of data storage technologies has emerged, but their success is limited and it poses a wide range of problems in the coming years. ln the interest oi‘ saving time and efficiency, many researchers believe that they have found the solution to this problem, either develop and add an intelligent touch to the available technology [Hadoop and REHDFS), or have discovered solutions. effective in the field of chemistry, DNA for example. The objectives ofthis article are to present a comparative study between two generations er data storage, a classic relational generation and other more advanced generation that we call NDSQL. Thus, a representation of the two future storage solutions with its advantages and value-added analyses by both approaches.