SQL versus NoSQL : comparison case MySQL versus MongoDB
Vatjalainen, Anna (2023)
2023
All rights reserved. This publication is copyrighted. You may download, display and print it for Your own personal use. Commercial use is prohibited.
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:amk-2023112230888
https://urn.fi/URN:NBN:fi:amk-2023112230888
Tiivistelmä
The growing volume of data and the demand for data-driven applications emphasizes the critical role of selecting an appropriate Database Management System (DBMS). This thesis addresses the significant impact of this decision on modern software functionality by exploring the key differences between SQL (Structured Query Language) and NoSQL (Not Only SQL) databases, specifically examining the case of MySQL and MongoDB.
The research has three main objectives: to thoroughly compare SQL (MySQL) and NoSQL (MongoDB) databases, examine their security performance, and understand the scenarios where one excels over the other.
In terms of implementation, the study employs a comparative research approach, focusing on theoretical aspects as well as considering real-life examples and case studies. The research involves analyzing data models, query languages, and security features of MySQL and MongoDB databases to draw comparisons and conclusions.
The key results and outputs provide a roadmap for selecting an optimal DBMS and enhancing data security. The study acknowledges that certain aspects may be left outside the scope of the analysis, such as specific industry considerations. Future work should focus on expanding the scope to include industry-specific challenges and evolving database technologies.
The research has three main objectives: to thoroughly compare SQL (MySQL) and NoSQL (MongoDB) databases, examine their security performance, and understand the scenarios where one excels over the other.
In terms of implementation, the study employs a comparative research approach, focusing on theoretical aspects as well as considering real-life examples and case studies. The research involves analyzing data models, query languages, and security features of MySQL and MongoDB databases to draw comparisons and conclusions.
The key results and outputs provide a roadmap for selecting an optimal DBMS and enhancing data security. The study acknowledges that certain aspects may be left outside the scope of the analysis, such as specific industry considerations. Future work should focus on expanding the scope to include industry-specific challenges and evolving database technologies.