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Technologies for Big Data

Technologies for Big Data
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Author(s): Kapil Bakshi (Cisco Systems Inc., USA)
Copyright: 2014
Pages: 22
Source title: Big Data Management, Technologies, and Applications
Source Author(s)/Editor(s): Wen-Chen Hu (University of North Dakota, USA)and Naima Kaabouch (University of North Dakota, USA)
DOI: 10.4018/978-1-4666-4699-5.ch001

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Abstract

This chapter provides a review and analysis of several key Big Data technologies. Currently, there are many Big Data technologies in development and implementation; hence, a comprehensive review of all of these technologies is beyond the scope of this chapter. This chapter focuses on the most popularly accepted technologies. The key Big Data technologies to be discussed include: Map-Reduce, NOSQL technology, MPP (Massively Parallel Processing), and In Memory Databases technologies. For each of these Big Data technologies, the following subtopics are discussed: the history and genesis of the Big Data technologies, problem set that this technology solves for Big Data analytics, the details of the technologies, including components, technical architecture, and theory of operations. This is followed by technical operation and infrastructure (compute, storage, and network), design considerations, and performance benchmarks. Finally, this chapter provides an integrated approach to the above-mentioned Big Data technologies.

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