Abstract
Graph databases are an emerging technology with the potential to support complex data-intensive applications. Existing works on designing graph models often take an intuitive approach. In this paper, we discuss why this can easily lead to performance degradation for application-specific queries, and illustrate this with the example of dynamic taxi ride-sharing. Our findings call for more sophisticated data modeling approaches. We propose a new filter-based graph model for dynamic taxi ride-sharing based on a thorough analysis of an existing intuitive graph model. In particular, we suggest a new modeling rule using filter nodes to improve the performance of mission-critical queries. We evaluate our proposed graph model using simulations with real-world data. The results demonstrate that our proposed filter-based model outperforms the intuitive graph model in terms of query performance.
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Steinmetz, D., Merz, F., Burmester, G., Ma, H., Hartmann, S. (2022). A Modeling Rule for Improving the Performance of Graph Models. In: Ralyté, J., Chakravarthy, S., Mohania, M., Jeusfeld, M.A., Karlapalem, K. (eds) Conceptual Modeling. ER 2022. Lecture Notes in Computer Science, vol 13607. Springer, Cham. https://doi.org/10.1007/978-3-031-17995-2_24
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