A Contingent Exploration on Big Data Tools

Abstract

In past few years, size of the data is growing exponentially by extreme fast rates, for instance, the size of data growth was ten times faster in the growth due to various means such as the data from mobile devices, remote sensing, sensing aerial devices, recording frequency of radio waves. Until most recently, most of the data was never analysed and most of the time it was discarded. The data stored requires lots of storage space whereas later due to lack of storage space the data is either ignored or deleted due to lack of storage space to process the data. Sometimes, we are even capable of storing the data but until that data is not processed, it is raw useless data to us because that will not be able to fetch with new insights. In the analysis, we face two types of challenges, first is the lack of storage space and second a suitable software to process this data. In this paper, we have discussed about the evolution of 4 V’s of big data, levels of big data tools, various data tools along with a comparative analysis of those tools on the basis of distinguished features like mode of software, data processing, language support, data flow security, latency and fault tolerance is also generalized for better understanding.