Neo4EMF : when big models are no longer an issue

Amine Benelallam 1, 2 Hugo Bruneliere 1, 2
1 ATLANMOD - Modeling Technologies for Software Production, Operation, and Evolution
LINA - Laboratoire d'Informatique de Nantes Atlantique, Département informatique - EMN, Inria Rennes – Bretagne Atlantique
Abstract : Handling effectively big EMF models has often been one of the main barriers that can retain from adopting modeling technologies in very large-scale complex systems. In this talk we present Neo4EMF, a Neo4j-based persistence framework allowing on-demand loading, storage, unloading and actual use of very large EMF models. Neo4EMF provides a No-SQL database persistence framework based on Neo4j, which is a transactional property-graph database that has proved having a remarkable running speed for connected data operations compared to relational databases. In terms of performance, Neo4EMF eases data access and storage not only in a manner to reduce time and memory usage but also to allow big EMF models to fit into a reduced amount of memory. This is made possible through a lightweight and on-demand loading mechanism. Moreover, Neo4EMF comes with a dirty saving mechanism allowing to store huge chunks of data even with limited memory resources.
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Conference papers
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https://hal.inria.fr/hal-01026219
Contributor : Hugo Bruneliere <>
Submitted on : Monday, July 21, 2014 - 10:14:33 AM
Last modification on : Thursday, May 16, 2019 - 1:26:02 PM

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Amine Benelallam, Hugo Bruneliere. Neo4EMF : when big models are no longer an issue. EclipseCon France 2014, Jun 2014, Toulouse, France. ⟨hal-01026219⟩

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