UMLtoGraphDB: Mapping Conceptual Schemas to Graph Databases

Conference paper

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

Part of the Lecture Notes in Computer Science book series (LNCS, volume 9974)
Cite this paper as:
Daniel G., Sunyé G., Cabot J. (2016) UMLtoGraphDB: Mapping Conceptual Schemas to Graph Databases. In: Comyn-Wattiau I., Tanaka K., Song IY., Yamamoto S., Saeki M. (eds) Conceptual Modeling. ER 2016. Lecture Notes in Computer Science, vol 9974. Springer, Cham

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, an abstraction 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.

Keywords

Database design UML OCL NoSQL Graph database Gremlin 

Copyright information

© Springer International Publishing AG 2016

Authors and Affiliations

  1. 1.AtlanMod TeamInria, Mines Nantes, LinaNantesFrance
  2. 2.ICREABarcelonaSpain
  3. 3.Internet Interdisciplinary Institute, UOCBarcelonaSpain

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