NoSQL Databases: Modern Data Systems for Big Data Analytics - Features, Categorization and Comparison

Authors

  • Atul Thakare CSE Department, Koneru Lakshmaiah Education Foundation, Guntur District, Andhra Pradesh, India https://orcid.org/0000-0003-3897-5973
  • Omprakash W. Tembhurne School of Computing, MIT Art Design and Technology University, Pune, Maharashtra, INDIA
  • Abhijeet R. Thakare MCA Department, Shri Ramdeobaba College of Engineering and Management, Nagpur, Maharashtra, India.
  • Soora Narasimha Reddy CSE Department, Kakatiya Institute of Technology and Science, Hasanparhty, Warangal, Telangana, India

DOI:

https://doi.org/10.32985/ijeces.14.2.10

Keywords:

Unstructured Data, NoSQL Database, Horizontal Scaling, Vertical Scaling, CAP Theorem, Weak Consistency

Abstract

Because of the massive utilization of the world wide web and the drastic use of electronic gadgets to access the online world, there is an exponential growth in the information produced by these hardware gadgets. The data produced by different sources, such as smart transportation, healthcare, and e-commerce, are large, complex, and heterogeneous. Therefore, storing and querying this data, coined "Big Data," is challenging. This paper compares relational databases with a few of the popular NoSQL databases. The performance of various databases in executing join queries, filter queries, and aggregate queries on large datasets are compared on a single node and multinode clusters. The experimental results demonstrate the suitability of NoSQL databases for Big Data Analytics and for supporting large userbase interactive web applications.

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Published

2023-02-17

How to Cite

[1]
A. Thakare, O. W. Tembhurne, A. R. Thakare, and S. N. Reddy, “NoSQL Databases: Modern Data Systems for Big Data Analytics - Features, Categorization and Comparison”, IJECES, vol. 14, no. 2, pp. 207-216, Feb. 2023.

Issue

Section

Original Scientific Papers