Leveraging Database Technologies for Efficient Data Modeling and Storage in Web Applications - Dhruv Patel, (International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 2024)
Today’s data-intensive digital environment is populated with web applications in every industry that hinge on a large amount of diverse and dynamic data, which requires sophisticated systems for managing this data in applications. The importance of data modelling and storage is discussed in this study the development of efficient, scalable, and reliable web applications. It is detailed in terms of data modeling fundamentals, such as the identification of the entities, mapping relationships, and optimizing the schema to ensure the data remains intact and the application logic is simple. It is a study that compares three major database technologies that are Relational (SQL), NoSQL, and NewSQL, and tries to compare their architecture, strengths, and ideal use cases. Moreover, it brings attention to recent database innovations, including cloud-native and serverless databases and AI and machine learning (ML) for self-managing of databases and data analytics. Schema optimization and all the rest of the strategies for storage data are also discussed. The paper synthesizes from current practices and emerging trends, and offers comprehensive insights to help developers and organizations make the best selection of data technologies that will help in improving overall application performance, data security, and real-time decision making.
Keywords: Database Technologies; RDBMS; NoSQL; Cloud Databases; Distributed Storage; Hybrid Models; Machine Learning (ML)