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Technologique
Volume 8 | Issue 1 | 2026 | 119 – 133
1College Instructor, Polytechnic University of the Philippines, Sta. Mesa, Manila, Philippines
2College Instructor, Mandaluyong City College of Science and Technology, Mandaluyong City, Philippines
Article History:
Initial submission: 19 June 2026
First decision: 28 June 2026
Revision received: 24 July 2026
Accepted for publication: 30 July 2026
Online release: 07 August 2026
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The increasing demand for efficient data management in modern web applications has highlighted the importance of selecting an appropriate database management system based on application requirements and workload characteristics. Although MySQL and MongoDB have been widely adopted in web development, limited empirical studies have evaluated their performance when integrated with the Laravel framework. This study compared MySQL and MongoDB in terms of installation and configuration requirements, database schema design characteristics, CRUD (Create, Read, Update, and Delete) performance, query execution performance, and scalability characteristics across varying dataset sizes. An exploratory quantitative experimental research design was employed using a Laravel-based prototype web application and identical datasets containing 1,000, 10,000, 50,000, and 100,000 records. Performance was evaluated by measuring the execution times of CRUD operations and query processing tasks using standardized experimental procedures. The findings revealed that MongoDB demonstrated superior average performance in data update (2,592.52 ms) and data deletion (1,043.74 ms) operations compared with MySQL’s 6,107.24 ms and 2,135.98 ms, respectively. Conversely, MySQL achieved better average performance in data insertion and data retrieval workloads, recording an average insert time of 5,560.26 ms and an average read time of 499.46 ms, compared with MongoDB’s 21,817.48 ms and 572.99 ms, respectively. Furthermore, MongoDB demonstrated significant performance advantages in simple, filtered, and complex query processing, reducing complex query execution times by 87.91% over MySQL, whereas MySQL maintained a 9.95% advantage in analytical aggregation queries. The results indicate that MySQL offers distinct advantages in native Laravel integration, data integrity, and relational data management, whereas MongoDB demonstrates strengths in schema flexibility, filtered data retrieval, and modification-heavy workloads. Scalability characteristics were inferred from execution-time trends observed across increasing dataset sizes. Overall, neither database management system was universally superior across all application scenarios. The findings provide framework-specific empirical evidence to assist software developers and system designers in selecting appropriate database technology for Laravel-based web applications.
Keywords: MySQL, MongoDB, Laravel, Relational Database, NoSQL Database, CRUD Performance, Query Performance, Scalability
APA (7th edition)
Bedis, S. M., Jr., & Amata, M. L. C. (2026). A comparative performance analysis of MySQL and MongoDB in Laravel-based web applications. Technologique, 8(1), 119–133. https://doi.org/10.62718/vmca.tech-gjtdsi.8.1.SC-0626-009.
Copyright @ 2026. The Author/s. Published by VMC Analytiks Multidisciplinary Journal News Publishing Services. A Comparative Performance Analysis of MySQL and MongoDB in Laravel-Based Web Applications © 2026 by Severino M. Bedis Jr. and Ma. Leonila C. Amata is an open access article licensed under Creative Commons Attribution (CC BY 4.0). This permits the copying, redistribution, remixing, transforming, and building upon the material in any medium or format for any purpose, even commercially, provided that appropriate credit is given to the copyright owner/s through proper and standard citation.
Severino M. Bedis Jr.: Conceptualization, Methodology, Software Development, Data Collection, Formal Analysis, Validation, Visualization, and Writing – Original Draft
Ma. Leonila C. Amata: Supervision, Methodology Review, Validation, Writing – Review and Editing, and Project Administration. All authors reviewed and approved the final manuscript.
This research received no external funding and was conducted as part of the academic requirements for the Master of Science in Information Technology program.
The authors declare no conflict of interest regarding the publication of this paper.
This study did not involve human participants, animals, personal data, or sensitive information. Therefore, ethics approval was not required. The datasets used were synthetically generated for benchmarking purposes.
All data generated or analyzed during this study are included in this published article. The datasets used in the experiments were generated through Laravel seeders and do not contain any personal or sensitive information. The source code and benchmarking procedures are available from the corresponding author upon reasonable request.
Artificial intelligence tools were utilized solely for language refinement, grammar checking, and manuscript editing assistance. All research design, implementation, data collection, analysis, interpretation, and conclusions were conducted and verified by the author.
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The views expressed in this article are those of the authors and do not necessarily reflect the views of the publisher. The publisher disclaims any responsibility for errors or omissions.