Publication at Faculty of Mathematics and Physics |
2022
Abstract
In this paper, we present our prototype implementation MM-infer that ensures inference of a common schema of multi-model data. It supports popular data models and all three types of their mutual combinations, i.e., inter-model references, the embedding of models, and cross-model redundancy.
Following the current trends, the implementation can efficiently process large amounts of data. To the best of our knowledge, ours is the first tool addressing schema inference in the world of multi-model databases.