Leading NoSQL models for handling Big Data: a brief review. (2016)

• Record Type: Journal Article
• Authors: Sharma, Sugam; Shandilya, Ritu; Patnaik, Srikanta; Mahapatra, Ashok
• Is Part Of: International journal of business information systems. Volume 22:Number 1(2016)
• Page Start: 1
• Page End: 25
• Publication Date: 2016
• Subjects: not only SQL -- NoSQL -- big data -- data models -- data modelling; Information storage and retrieval systems -- Business -- Periodicals; Business -- Data processing -- Periodicals; Management information systems -- Periodicals; System design -- Periodicals; System analysis -- Periodicals; 651.8
• Languages: English
• ISSNs: 1746-0972

Abstract

Today, in data science, the large, complex, structured or unstructured, and heterogeneous data has gained significant attention. The data is being generated at a very rapid pace through various disparate potential resources and sensors, scientific instruments, and internet, especially the social media, are just to name a few. The considerable velocity of the volume expansion of the data possesses the serious challenges for the existing data processing systems. In this paper, we review some of the modern data models that claim to process the extremely large data such as Big Data (of petabyte size) in reliable and efficient way and are the leading contributors in NoSQL (largely being translated as 'not only SQL') era.