Benchmarking Cloud-Native ETL Tools Performance, Cost, and Scalability

Mr. Raghavendar Nellikondi, Mr. Reddaiah Kasturi

Benchmarking Cloud-Native ETL Tools Performance, Cost, and Scalability

Authors

Mr. Raghavendar Nellikondi, Mr. Reddaiah Kasturi

Keywords:

Cloud-native ETL, Performance benchmarking, Cost efficiency, Scalability analysis, Data engineering.

Abstract

This work evaluates the performance, cost and their scalability for four popular cloud native ETLtools on public clouds. We were able to process ordered/equijoin/GroupBy datasets of size 10 GBup to 2 TB (both structured and semi-structured data) in a controlled experimental environment,using the same compute/network settings

References

Guo, Y.; Varbanescu, A.L.; Iosup, A.; Martella, C.; Willke, T.L. Benchmarking graphprocessing platforms: A vision. In Proceedings of the 5th ACM/SPEC International Conference on Performance Engineering, Dublin, Ireland, 22–26 March 2014; pp. 289292. [Google Scholar]

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Published

2024-12-19

How to Cite

Mr. Raghavendar Nellikondi, Mr. Reddaiah Kasturi. (2024). Benchmarking Cloud-Native ETL Tools Performance, Cost, and Scalability. Journal of Computational Analysis and Applications (JoCAAA), 33(08), 7433–7447. Retrieved from https://eudoxuspress.com/index.php/pub/article/view/4683