IJBTT

Comparative Analysis of Spark Connect and REST APIs: Architecture, Performance, and Use Cases
	© 2025 by IJCTT Journal
	Volume-73 Issue-4
	Year of Publication : 2025
	Authors : Ajinkya Potdar
	DOI :  10.14445/22312803/IJCTT-V73I4P115

How to Cite?

Ajinkya Potdar, "Comparative Analysis of Spark Connect and REST APIs: Architecture, Performance, and Use Cases," International Journal of Computer Trends and Technology, vol. 73, no. 4, pp. 108-113, 2025. Crossref, https://doi.org/10.14445/22312803/IJCTT-V73I4P115

Abstract
This paper presents a comparative analysis of Spark Connect and REST APIs, two prominent technologies facilitating the communication between applications and data sources. Spark Connect, a relatively new feature in Apache Spark, introduces a client-server architecture that enhances several key tenets of the overall solution while supporting multiple programming languages. On the other hand, REST APIs, a traditional solution, remain the backbone of web services, offering a standardized, scalable, and stateless approach to data exchange. This research contributes to the field by exploring the architectural differences, communication protocols, data handling mechanisms, scalability, security implications, and performance trade-offs of both technologies. Spark Connect excels in interactive data analysis and remote Spark development, whereas REST APIs dominate web services, microservices, and mobile app integration. By virtue of the contextual analysis and information, we assess the strengths and limitations of both solutions, enabling organizations to make informed decisions to select the appropriate technology for their use cases. This analysis emphasizes the importance of adopting the right solution to ensure cost and performance optimization in a secure environment.

Keywords
Big data, Data analytics, Spark Connect, REST API, Data access methods.

Reference

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