UMLtoGraphDB: Mapping conceptual schemas to graph databases

Other authors

Institut National de Recherche en Informatique et en Automatique (INRIA)

Universitat Oberta de Catalunya. Internet Interdisciplinary Institute (IN3)

Publication date

2018-05-14T08:45:37Z

2018-05-14T08:45:37Z

2016-10-07



Abstract

The need to store and manipulate large volume of (unstructured) data has led to the development of several NoSQL databases for better scalability. Graph databases are a particular kind of NoSQL databases that have proven their efficiency to store and query highly interconnected data, and have become a promising solution for multiple applications. While the mapping of conceptual schemas to relational databases is a well-studied field of research, there are only few solutions that target conceptual modeling for NoSQL databases and even less focusing on graph databases. This is specially true when dealing with the mapping of business rules and constraints in the conceptual schema. In this article we describe a mapping from UML/OCL conceptual schemas to Blueprints, anabstraction layer on top of a variety of graph databases, and Gremlin, a graph traversal language, via an intermediate Graph metamodel. Tool support is fully available.

Document Type

Article


Submitted version

Language

English

Publisher

Lecture Notes in Computer Science

Related items

Lecture Notes in Computer Science, 2016, 9974

https://doi.org/10.1007/978-3-319-46397-1_33

Recommended citation

Daniel, G., Sunyé, G. & Cabot, J. (2016). UMLtoGraphDB: Mapping Conceptual Schemas to Graph Databases. Lecture Notes in Computer Science, 9974(), 430-444. doi: 10.1007/978-3-319-46397-1_33

0302-9743

10.1007/978-3-319-46397-1_33

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