Open Access

ARTICLE

Query Optimization Framework for Graph Database in Cloud Dew Environment

Tahir Alyas¹, Ali Alzahrani², Yazed Alsaawy², Khalid Alissa³, Qaiser Abbas², Nadia Tabassum^4,*

1 Department of Computer Science, Lahore Garrison University, Lahore, Pakistan
2 Faculty of Computer Science and Information Systems Islamic University Madinah, Madinah, 42351, Saudi Arabia
3 Networks and Communications Department, College of Computer Science and Information Technology, Imam Abdulrahman Bin Faisal University, P.O. Box 1982, Dammam, 31441, Saudi Arabia
4 Department of Computer Science, Virtual University of Pakistan, Lahore, Pakistan

* Corresponding Author: Nadia Tabassum. Email:

Computers, Materials & Continua 2023, 74(1), 2317-2330. https://doi.org/10.32604/cmc.2023.032454

Received 18 May 2022; Accepted 12 July 2022; Issue published 22 September 2022

Abstract

The query optimizer uses cost-based optimization to create an execution plan with the least cost, which also consumes the least amount of resources. The challenge of query optimization for relational database systems is a combinatorial optimization problem, which renders exhaustive search impossible as query sizes rise. Increases in CPU performance have surpassed main memory, and disk access speeds in recent decades, allowing data compression to be used—strategies for improving database performance systems. For performance enhancement, compression and query optimization are the two most factors. Compression reduces the volume of data, whereas query optimization minimizes execution time. Compressing the database reduces memory requirement, data takes less time to load into memory, fewer buffer missing occur, and the size of intermediate results is more diminutive. This paper performed query optimization on the graph database in a cloud dew environment by considering, which requires less time to execute a query. The factors compression and query optimization improve the performance of the databases. This research compares the performance of MySQL and Neo4j databases in terms of memory usage and execution time running on cloud dew servers.

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Keywords

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