An Extended Classification and Comparison of NoSQL Big Data Models (1509.08035v2)

Abstract: In last few years, the volume of the data has grown manyfold. The data storages have been inundated by various disparate potential data outlets, leading by social media such as Facebook, Twitter, etc. The existing data models are largely unable to illuminate the full potential of Big Data; the information that may serve as the key solution to several complex problems is left unexplored. The existing computation capacity falls short for the increasingly expanded storage capacity. The fast-paced volume expansion of the unorganized data entails a complete paradigm shift in new age data computation and witnesses the evolution of new capable data engineering techniques such as capture, curation, visualization, analyses, etc. In this paper, we provide the first level classification for modern Big Data models. Some of the leading representatives of each classification that claim to best process the Big Data in reliable and efficient way are also discussed. Also, the classification is further strengthened by the intra-class and inter-class comparisons and discussions of the undertaken Big Data models.