Parametric Analysis of Cloud Data Partitioning Techniques: Review Paper

Authors

  • Kaur K University College of Computer Applications, Guru Kashi University, Talwandi Sabo, Punjab, India
  • Laxmi V University College of Computer Applications, Guru Kashi University, Talwandi Sabo, Punjab, India

DOI:

https://doi.org/10.26438/ijcse/v6i9.881884

Keywords:

Horizontal partitioning, Vertical partitioning, Workload Driven partitioning, Communication cost, Complexity of search, Quality, Scalibility

Abstract

Technology makes life easier but at the same time generating bundles of data which is difficult to manage in traditional data stores. To manage this huge data, new data stores called NoSQL came into existence, they resolve the problem of data management by using partitioning. This paper discusses different partitioning techniques named horizontal, Vertical and Workload Driven Partitioning. Focus of this paper is to compare these partitioning techniques on the bases of important parameters named communication cost, complexity of search, quality and scalability. It provides the result on the basis of analysis which helps to choose the relevant partitioning technique.

References

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Published

2025-11-15
CITATION
DOI: 10.26438/ijcse/v6i9.881884
Published: 2025-11-15

How to Cite

[1]
K. Kaur and V. Laxmi, “Parametric Analysis of Cloud Data Partitioning Techniques: Review Paper”, Int. J. Comp. Sci. Eng., vol. 6, no. 9, pp. 881–884, Nov. 2025.

Issue

Vol. 6 No. 9 (2018): IJCSE September Editor

Section

Review Article

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