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Journal Articles Knowledge and Information Systems (KAIS) Year : 2023

Logical design of multi-model data warehouses


Multi-model DBMSs, which support different data models with a fully integrated backend, have been shown to be beneficial to data warehouses and OLAP systems. Indeed, they can store data according to the multidimensional model and, at the same time, let each of its elements be represented through the most appropriate model. An open challenge in this context is the lack of methods for logical design. Indeed, in a multi-model context, several alternatives emerge for the logical representation of dimensions and facts. The goal of this paper is to devise a set of guidelines for the logical design of multi-model data warehouses so that the designer can achieve the best trade-off between features such as querying, storage, and ETL. To this end, for each model considered (relational, document-based, and graph-based) and for each type of multidimensional element (e.g., non-strict hierarchy) we propose some solutions and carry out a set of intra-model and inter-model comparisons. The resulting guidelines are then tested on a case study that shows all types of multidimensional elements.
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Dates and versions

hal-04072544 , version 1 (07-08-2023)





Sandro Bimonte, Enrico Gallinucci, Patrick Marcel, Stefano Rizzi. Logical design of multi-model data warehouses. Knowledge and Information Systems (KAIS), 2023, 65 (3), pp.1067-1103. ⟨10.1007/s10115-022-01788-0⟩. ⟨hal-04072544⟩
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