Bivariate, cluster, and suitability analysis of NoSQL solutions for big graph applications

Khan, Samiya; Liu, Xiufeng; Ali, Syed Arshad; Alam, Mansaf

doi:10.1016/bs.adcom.2021.09.006

Cited by 1 publication

(1 citation statement)

References 135 publications

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“…The proposed methodology abridges the gap of this paper by evaluating the performance using these two metrics. S. Khan et al [12] analyze and organize 80 NoSQL technologies for easier comprehension. These solutions are classified, compared, and used on huge graphs in six categories.…”

Section: Literature Reviewmentioning

confidence: 99%

A Novel Approach of Latency and Energy Efficiency Analysis of IIoT With SQL and NoSQL Databases Communication

Kenitar,

Arioua,

Yahyaoui

2023

IEEE Access

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Industrial Internet of Things (IIoT)-enabled production facilities generate vast amounts of data, which, if harnessed effectively, can substantially enhance manufacturing efficiency through latency reduction. The selection of the appropriate data storage technology is a pivotal consideration in achieving this objective. While prior studies have examined SQL and NoSQL databases in terms of latency and energy efficiency, these evaluations have not been conducted specifically within the context of IIoT. This paper aims to fill this research gap by conducting a rigorous comparison of SQL and NoSQL databases, focusing on their performance latency and energy efficiency when interfaced with IoT nodes. By elucidating these relationships, our research offers actionable insights that can guide IIoT-enabled manufacturing facilities in optimizing their operations. Specifically, the paper aids in the selection of the most suitable database technology, thereby contributing to latency minimization and efficiency maximization in industrial settings.

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Section: Literature Reviewmentioning

confidence: 99%