Original scientific paper
https://doi.org/10.32985/ijeces.14.2.10
NoSQL Databases: Modern Data Systems for Big Data Analytics - Features, Categorization and Comparison
Atul Thakare
; CSE Department, Koneru Lakshmaiah Education Foundation, Guntur District, Andhra Pradesh, India
Omprakash W. Tembhurne
orcid.org/0000-0003-0141-2077
; 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
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.
Keywords
Unstructured Data; NoSQL Database; Horizontal Scaling; Vertical Scaling; CAP Theorem; Weak Consistency;
Hrčak ID:
294590
URI
Publication date:
27.2.2023.
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