Analisis Perbandingan Struktur Data Dan Kompleksitas Koding Antara MySQL Dan MongoDB Pada Pengembangan Aplikasi Blog
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Abstract
The dominance of Relational Database Management Systems (RDBMS) often introduces coding inefficiencies when handling hierarchical data structures, such as commenting features in modern web development. This study compares data structure design efficiency and coding complexity between MySQL and MongoDB within the context of blog application development. Employing a comparative experimental approach, the research simulates a Node.js-based article management module using a hybrid dataset that combines structured user profiles with dynamic volumes of nested comments. The analysis reveals significant architectural distinctions: MySQL necessitates strict normalization across five physical tables and complex join operations, whereas MongoDB leverages an embedded document model that eliminates the need for multi-table relations. Quantitatively, MongoDB demonstrated faster average read execution times (7.9 ms) compared to MySQL (10.7 ms) and yielded JSON data structures directly compatible with application objects, effectively resolving impedance mismatch issues. The study concludes that MongoDB offers superior developer productivity for use cases involving nested data, while MySQL remains the recommended choice for systems prioritizing strict referential integrity validation.
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