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Title: NeoEMF: a multi-database model persistence framework for very large models
Author: Daniel, Gwendal
Sunyé, Gerson
Benelallam, Amine
Tisi, Massimo
Vernageau, Yoann
Gómez Águila, Abel
Cabot Sagrera, Jordi  
Keywords: model persistence
large models
Issue Date: Oct-2016
Publisher: CEUR Workshop Proceedings
Citation: Daniel, G., Sunye, G.,Benelallam, A., Tisi, M., Vernageau, Y., Gomez, A., Cabot, J. (2016). "NeoEMF: a multi-database model persistence framework for very large models". CEUR Workshop Proceedings, 1725, p. 1-7. ISSN 1613-0073.
Abstract: The growing use of Model Driven Engineering (MDE) techniques in industry has emphasized scalability of existing model persistence solutions as a major issue. Specifically, there is a need to store, query, and transform very large models in an efficient way. Several persistence solutions based on relational and NoSQL databases have been proposed to achieve scalability. However, existing solutions often rely on a single data store, which suits a specific modeling activity, but may not be optimized for other use cases. In this article we present NEOEMF, a multi-database model persistence framework able to store very large models in key-value stores, graph databases, and wide column databases. We introduce NEOEMF core features, and present the different data stores and their applications. NEOEMF is open source and available online.
Language: English
ISSN: 1613-0073MIAR
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