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Modeling and Indexing Spatiotemporal Trajectory Data in Non-Relational Databases

Modeling and Indexing Spatiotemporal Trajectory Data in Non-Relational Databases

Berkay Aydin, Vijay Akkineni, Rafal A. Angryk
Copyright: © 2016 |Pages: 30
ISBN13: 9781466698345|ISBN10: 1466698349|EISBN13: 9781466698352
DOI: 10.4018/978-1-4666-9834-5.ch006
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MLA

Aydin, Berkay, et al. "Modeling and Indexing Spatiotemporal Trajectory Data in Non-Relational Databases." Managing Big Data in Cloud Computing Environments, edited by Zongmin Ma, IGI Global, 2016, pp. 133-162. https://doi.org/10.4018/978-1-4666-9834-5.ch006

APA

Aydin, B., Akkineni, V., & Angryk, R. A. (2016). Modeling and Indexing Spatiotemporal Trajectory Data in Non-Relational Databases. In Z. Ma (Ed.), Managing Big Data in Cloud Computing Environments (pp. 133-162). IGI Global. https://doi.org/10.4018/978-1-4666-9834-5.ch006

Chicago

Aydin, Berkay, Vijay Akkineni, and Rafal A. Angryk. "Modeling and Indexing Spatiotemporal Trajectory Data in Non-Relational Databases." In Managing Big Data in Cloud Computing Environments, edited by Zongmin Ma, 133-162. Hershey, PA: IGI Global, 2016. https://doi.org/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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