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Graph Data: The Next Frontier in Big Data Modeling for Various Domains

Affiliations

  • Department of MCA, Shri Chimanbhai Patel Post Graduate Institute of Computer Applications, S. G. Highway, Ahmedabad – 380015, Gujarat, India
  • Department of MCA, Acharya Motibhai Patel Institute of Computer Studies, Ganpat University, Ganpat Vidyanagar, Mehsana – 384012, Gujarat, India

Abstract


Graph is considered as next frontier in the era of Big data due to its flexibility and self-explaining property. The prime objective of this research is to reveal graph database as an alternative of traditional relation database in the field of database. This research illustrates potential of graph structure for diversified modeling along with its convenience for various domains. Extensive literature review demonstrates use of diversified graph structures as means of data storage and analysis as it can cope up any kind of complex structures ranging from multi linked web data, complex chemical structure, gene data, network structure, social network, e-commerce to text data. A formal conclusion of this review revealed use of various graph models according to state-of-affairs of various domains as well as data modeling challenges and complexity of Big data. This investigation anticipates use of an appropriate graph structure and provides guidelines for solving data modeling challenges for structure, semi structure and unstructured data. The diversified graph structure along with its characteristics has been suggested for real world problems of various domains. This research could lend a helping hand to anyone who wants to implement graph data model for their data management challenges and computational problems.

Keywords

Big Data, Graph Data, NoSQL, Property Graph

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