An experimental analysis of Data Management Approaches for Spatiotemporal Data in Visual Analysis Systems

• Lorenna Christ'na Nascimento Fluminense Federal University (UFF)
• Marcos Lage Fluminense Federal University (UFF)
• Daniel de Oliveira Fluminense Federal University (UFF)

DOI: https://doi.org/10.5753/sbbd.2021.17899

Abstract

Over the last years, visual analytics systems have gained importance not only for presenting final results, but also for assisting in interactive analysis and decision-making processes. Such systems require efficient access to data, so that response times does not interfere with the user's ability to observe and analyze. Concurrently, research in the database domain has proposed solutions that can be used to support visualization systems. This paper presents a study of data management approaches to support interactive visualizations. We compared the performance of PostgreSQL, MonetDB, and Spark SQL to process multiple spatiotemporal queries common in visual analytics system. This study showed that Spark SQL presented the best performance for the chosen queries.

Keywords: Visualization, Spatiotemporal Data, Interactive Analysis

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