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

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.
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Submitted on : Wednesday, January 25, 2017 - 5:27:52 PM
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  • HAL Id : hal-01436047, version 1

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Gwendal Daniel, Gerson Sunyé, Amine Benelallam, Massimo Tisi, Yoann Vernageau, et al.. NeoEMF: a Multi-database Model Persistence Framework for Very Large Models. Proceedings of the MoDELS 2016 Demo and Poster Sessions co-located with ACM/IEEE 19th International Conference on Model Driven Engineering Languages and Systems (MoDELS 2016), Oct 2016, Saint-Malo, France. ⟨hal-01436047⟩

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