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The primary objective of this paper is to present detailed analysis of various platforms suitable for Big Data processing. In this paper, various software frameworks available for Big Data analytics are surveyed and in-detail assessment of their strengths and weaknesses is discussed. In addition to this, widely used data mining algorithm are discussed for their adaptation for Big Data analysis w.r.t their suitability for handling real-world application problems. Future trends of Big Data processing and analytics can be predicted with effective implementation of these well established and widely used data mining algorithms by considering the strengths of software frameworks and platforms available. Hybrid approaches (integration of two or more platforms) may be more appropriate for a specific data mining algorithm and can be highly adaptable as well as perform real-time processing.
Londhe et al. (Tue,) studied this question.
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