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NextGen Multi-Model Databases in Semantic Big Data Architectures

Publication at Faculty of Mathematics and Physics |
2020

Abstract

In this vision paper, we discuss the potential of a new generation of multi-model database systems as data backends in such settings. Discussing a specific example scenario, we show how this family of database systems allows for agile and flexible schema management.

We also identify open research challenges in generating sound triple-views from data stored in interlinked models, as a basis for SPARQL querying. We then conclude with a general overview of multi-model data management systems, to provide a wider scope of the problem domain.