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Modeling and Indexing Spatiotemporal Trajectory Data in Non-Relational Databases
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Author(s): Berkay Aydin (Georgia State University, USA), Vijay Akkineni (Georgia State University, USA)and Rafal A. Angryk (Georgia State University, USA)
Copyright: 2016
Pages: 30
Source title:
Managing Big Data in Cloud Computing Environments
Source Author(s)/Editor(s): Zongmin Ma (Nanjing University of Aeronautics and Astronautics, China)
DOI: 10.4018/978-1-4666-9834-5.ch006
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Abstract
With the ever-growing nature of spatiotemporal data, it is inevitable to use non-relational and distributed database systems for storing massive spatiotemporal datasets. In this chapter, the important aspects of non-relational (NoSQL) databases for storing large-scale spatiotemporal trajectory data are investigated. Mainly, two data storage schemata are proposed for storing trajectories, which are called traditional and partitioned data models. Additionally spatiotemporal and non-spatiotemporal indexing structures are designed for efficiently retrieving data under different usage scenarios. The results of the experiments exhibit the advantages of utilizing data models and indexing structures for various query types.
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