Efficient Data Handling with LINQ, SQL, and JSON in C# Applications
Keywords:
C# applications, LINQ, SQL, JSON serialization, NET performance, data optimizationAbstract
Efficient data management is a critical concern in contemporary software engineering, particularly within the .NET ecosystem, where applications frequently interact with relational databases, in-memory collections, and semi-structured formats such as JSON. This study systematically evaluates the performance and operational characteristics of three prominent data-handling approaches in C#: Language Integrated Query (LINQ), Structured Query Language (SQL), and JSON-based serialization. Through controlled experiments on representative datasets, the research assesses execution time, memory utilization, scalability, and serialization efficiency. The results demonstrate that SQL consistently achieves superior performance for large-scale relational operations, whereas LINQ enhances code expressiveness and maintainability, albeit with increased memory allocations in complex queries. JSON processing performance is highly dependent on parsing strategy and data complexity. Based on these insights, the study proposes a hybrid data-handling framework that strategically combines LINQ, SQL, and JSON techniques to optimize both system responsiveness and resource efficiency. This framework provides practical guidance for developers and architects seeking to improve the performance and maintainability of data-intensive C# applications.
Downloads
References
A. Gruca and P. Podsiadło, "Performance Analysis of. NET Based Object–Relational Mapping Frameworks," in International Conference: Beyond Databases, Architectures and Structures, 2014: Springer, pp. 40-49.
A. Ullah, M. Usman, M. F. Abrar, N. Ullah, I. A. Shah, and M. F. Nadeem, "Systematic performance, and Security evaluation of. NET models for accessing database," VFAST Transactions on Software Engineering, vol. 9, no. 4, pp. 18-24, 2021.
A. E. Güvercin and B. Avenoglu, "Performance analysis of object-relational mapping (orm) tools in. net 6 environment," Bilişim Teknolojileri Dergisi, vol. 15, no. 4, pp. 453-465, 2022.
T. Wiatrowski, "Comparative Analysis of ORM Systems for the. NET Platform," Journal of Computer Sciences Institute, vol. 31, pp. 97-102, 2024.
J. C. Viotti and M. Kinderkhedia, "A benchmark of JSON-compatible binary serialization specifications," arXiv preprint arXiv:2201.03051, 2022.
W. Wei et al., "An Extensive Study on Text Serialization Formats and Methods," arXiv preprint arXiv:2505.13478, 2025.
S. Cvetković and D. Janković, "A comparative study of the features and performance of orm tools in a. net environment," in International Conference on Object and Databases, 2010: Springer, pp. 147-158.
J. Cheney, S. Lindley, and P. Wadler, "A practical theory of language-integrated query," ACM SIGPLAN Notices, vol. 48, no. 9, pp. 403-416, 2013.
N. Nurseitov, M. Paulson, R. Reynolds, and C. Izurieta, "Comparison of JSON and XML data interchange formats: a case study," Caine, vol. 9, pp. 157-162, 2009.
P. Kalvoda, "Implementace a evaluace protokolu CBOR," 2015.
P. Borra, "Securing cloud infrastructure: An in-depth analysis of microsoft azure security," International Journal of Advanced Research in Science, Communication and Technology (IJARSCT) Volume, vol. 4, 2024.
M. A. Junior, P. Appiahene, O. Appiah, and K. Adu, "Cloud data privacy protection with homomorphic algorithm: a systematic literature review," Journal of Cloud Computing, 2025.
