Downloads: 0
India | Data and Knowledge Engineering | Volume 14 Issue 10, October 2025 | Pages: 49 - 52
A Comparative Study of SAS vs. R vs. Python vs. MATLAB - on Handling Large Datasets
Abstract: With the exponential growth of data in diverse domains, the ability of statistical and computational tools to handle large datasets efficiently has become critical. Among the most widely used platforms in data science are SAS, R, Python, and MATLAB, each offering unique strengths and limitations. This study presents a comparative analysis of these tools in terms of scalability, computational efficiency, memory management, community support, and cost-effectiveness when working with large datasets. By synthesizing existing benchmarks and empirical results, this paper highlights trade-offs that practitioners and organizations must consider while selecting a tool for big data analytics.
Keywords: Big Data Analytics, statistical tools comparison, scalability and efficiency, memory management, cost effectiveness
How to Cite?: Dr. Ashok Jahagiradar, "A Comparative Study of SAS vs. R vs. Python vs. MATLAB - on Handling Large Datasets", Volume 14 Issue 10, October 2025, International Journal of Science and Research (IJSR), Pages: 49-52, https://www.ijsr.net/getabstract.php?paperid=SR251001071924, DOI: https://dx.doi.org/10.21275/SR251001071924