A Comparative Performance Analysis of MySQL and MongoDB in Laravel-Based Web Applications

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.