Beierlieb, LukasIffländer, LukasPrantl, ThomasKounev, SamuelHerrmann, Andrea2023-11-302023-11-3020230720-8928https://dl.gi.de/handle/20.500.12116/43248This paper compares the execution speed of R, Python, and Rust implementations in the context of data processing. A real-world data processing task in the form of an aggregation of benchmark measure ment results was implemented in each language, and the execution times were measured. Rust and Python showed significantly superior performance compared to the R implementation. Further, we compared the results of different Python interpreters (the most recent versions of CPython and PyPy), also resulting in measurable variations. Finally, a study of the effectiveness of multithreading was performed.enSPPbenchmarksoftware performancedata processingpythonR languagerustText/Conference Paper