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SQL or NoSQL—Practical Aspect and Rational behind Choosing Data Stores

DOI: 10.4236/jcc.2024.128001, PP. 1-20

Keywords: SQLData Stores, NO-SQLData Stores, ACID, BASE, RUM Conjecture

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Abstract:

Data storage solutions are a crucial aspect of any application, significantly impacting data management and system performance. This article explores the rationale behind utilizing both SQL and NoSQL databases, addressing key questions about when each type is preferable. The background emphasizes the importance of selecting the appropriate database technology to meet specific application requirements. The purpose of this research is to provide a comprehensive guide for choosing between SQL and NoSQL databases based on various factors, including workload characteristics, scalability needs, and consistency requirements. To achieve this, we examine different strategies for implementing SQL and NoSQL databases in large-scale distributed applications and systems. The research method involves a comparative analysis of the features, advantages, and limitations of both database types. We specifically focus on scenarios involving read-heavy versus write-heavy systems and the trade-offs between availability and consistency. The results of this research indicate that SQL databases, with their relational structure and ACID compliance, are ideal for applications requiring complex queries and data integrity. In contrast, NoSQL databases, offering schema flexibility and horizontal scalability, are better suited for managing extensive datasets and high-velocity data ingestion. In conclusion, the selection of a database depends on the specific needs of the application. SQL databases are preferred for transactional systems with complex relationships, while NoSQL databases excel in scenarios demanding flexibility and scalability. The study provides insights into hybrid approaches, leveraging both database types to optimize system performance.

References

[1]  Athanassoulis, M., Kester, M.S., Maas, L.M., RaduStoica, et al. (2016) Designing Access Methods: The RUM Conjecture. EDBT, 2016, 461-466.
[2]  Kleppmann, M. (2017) Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems. O’Reilly Media, Inc.
[3]  Gierke, O. (2012) Spring Data JPA-Reference Documentation.
https://docs.spring.io/spring-data/jpa/docs/current/reference/html/
[4]  Shivakumar, S.K. and Sethii, S. (2019) Introduction to Digital Experience Platforms. In: Building Digital Experience Platforms. Apress.
https://doi.org/10.1007/978-1-4842-4303-9_1
[5]  Pollack, M, Gierke, O., Risberg, T., et al. (2012) Spring Data: Modern Data Access for Enterprise Java. O’Reilly Media, Inc.
[6]  Meier, A., and Kaufmann, M. (2019) SQL & NoSQL Databases. Springer Fachmedien Wiesbaden.
[7]  Venkatraman, S., Kaspi, K.F.S. and Venkatraman, R. (2016) SQL versus Nosql Movement with Big Data Analytics. International Journal of Information Technology and Computer Science, 8, 59-66.
https://doi.org/10.5815/ijitcs.2016.12.07
[8]  Parker, Z., Poe, S. and Vrbsky, S.V. (2013). Comparing NoSQL MongoDB to an SQL DB. Proceedings of the 51st ACM Southeast Conference, Savannah, 4-6 April 2013, 1-5.
https://doi.org/10.1145/2498328.2500047
[9]  Shivakumar, S.K., and Sethii, S. (2019) Building Digital Experience Platforms: A Guide to Developing Next-Generation Enterprise Applications. APress.
[10]  Petrov, A. (2019) Database Internals: A Deep Dive into How Distributed Data Systems Work. O’Reilly Media.

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