NeoEMF: A Multi-database Model Persistence Framework for Very Large Models - Archive ouverte HAL
Article Dans Une Revue Science of Computer Programming Année : 2017

NeoEMF: A Multi-database Model Persistence Framework for Very Large Models

Résumé

The growing role 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, they often rely on a single data store, which suits a specific modeling activity, but may not be optimized for other use cases. This paper presents NEOEMF, a tool that tackles this issue by providing a multi-database model persistence framework. Tool website: http://www.neoemf.com
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Dates et versions

hal-01589588 , version 1 (18-09-2017)

Identifiants

Citer

Gwendal Daniel, Gerson Sunyé, Amine Benelallam, Massimo Tisi, Yoann Vernageau, et al.. NeoEMF: A Multi-database Model Persistence Framework for Very Large Models. Science of Computer Programming, 2017, ⟨10.1016/j.scico.2017.08.002⟩. ⟨hal-01589588⟩
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