Classification and comparison of NoSQL big data models

TLDR

Big data’s rapid growth and complexity expose limitations in current data models and computational capacity, prompting a shift toward new data engineering techniques. The study aims to present a first‑level classification of leading NoSQL data models. The authors classify NoSQL models and enhance the taxonomy with intra‑ and inter‑class comparisons and discussions.

Abstract

In the data science age, the decision-making processes are largely data dependent. Though, the concept of big data is in the midst of evolution with great research and business opportunities, the challenges are enormous and growing equally too. This motivates various scientific disciplines to conglomerate their efforts for deep exploration of all dimensions of big data to procure evolutionary outcomes. The existing data models are largely unable to illuminate the full potential of big data. The existing computation capacity falls short for the increasingly expanded storage capacity. The fast-paced volume expansion of the unorganised data entails a complete paradigm shift in new age data computation and witnesses the evolution of new capable data engineering techniques. In this paper, we provide the first level classification for some modern, leading NoSQL representatives. Also, the classification is further strengthened by the intra-class and inter-class comparisons and discussions of the undertaken models.