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Architecture for Big Data Storage in Different Cloud Deployment Models
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Author(s): Chandu Thota (Infosys Ltd., India), Gunasekaran Manogaran (Vellore Institute of Technology, India), Daphne Lopez (Vellore Institute of Technology, India)and Revathi Sundarasekar (Priyadarshini Engineering College, India)
Copyright: 2018
Pages: 31
Source title:
Handbook of Research on Big Data Storage and Visualization Techniques
Source Author(s)/Editor(s): Richard S. Segall (Arkansas State University, USA)and Jeffrey S. Cook (Independent Researcher, USA)
DOI: 10.4018/978-1-5225-3142-5.ch008
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Abstract
Cloud Computing is a new computing model that distributes the computation on a resource pool. The need for a scalable database capable of expanding to accommodate growth has increased with the growing data in web world. More familiar Cloud Computing vendors such as Amazon Web Services, Microsoft, Google, IBM and Rackspace offer cloud based Hadoop and NoSQL database platforms to process Big Data applications. Variety of services are available that run on top of cloud platforms freeing users from the need to deploy their own systems. Nowadays, integrating Big Data and various cloud deployment models is major concern for Internet companies especially software and data services vendors that are just getting started themselves. This chapter proposes an efficient architecture for integration with comprehensive capabilities including real time and bulk data movement, bi-directional replication, metadata management, high performance transformation, data services and data quality for customer and product domains.
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