Database system comparison based on spatiotemporal functionality

What is it about?

The amount of sources and sheer volumes of spatiotemporal data have met an unprecedented growth during the last decade. As a consequence, a rapidly increasing number of applications are seeking to generate value by crunching those data. The development of a system that will tap into the potential value of the spatiotemporal big data analysis for a multitude of applications remains one of the biggest challenges in computer engineering. This paper delves into the key-characteristics of the most prominent suchlike systems. In particular, it provides a thorough analysis of NoSQL datastores as well as a traditional relational database system in terms of their geospatial querying capabilities.

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Photo by Taylor Vick on Unsplash

Photo by Taylor Vick on Unsplash

Why is it important?

The goal of this paper is to highlight these spatio-temporal functionalities of DBMSs and present the key architectural characteristics that are supporting them. It goes on to perform a comparison between a relational database system and several widely used NoSQL datastores across those characteristics. Based on the litera- ture review and to the best of our knowledge the most prominent differences concerning geospatial support for these data stores, are their data model and a number of geospatial capabilities. Such capabilities relate to geospatial indexing used, the geometry types supported and the spatial query operators performed.