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Unifying categorical representation of multi-model data

Publication at Faculty of Mathematics and Physics |
2022

Abstract

The support for multi-model data has become a standard for most of the existing DBMSs. The tools for database design are general enough to cover multiple models, too.

However, the step from a conceptual (e.g., ER or UML) schema to a logical multi-model schema of a DBMS (or their combination) is not straightforward. In this paper, we show how category theory can be used for representation of multi-model data and schema and how the mutual mapping between the categorical representation and logical models of particular DBMSs can be designed.

For this purpose we define the notion of an access path which enables to specify the mapping for all the currently popular models. To demonstrate advantages of the proposal we introduce framework MM-cat which applies the proposed approaches on MongoDB and PostgreSQL.