Efficient Persistence and Query Techniques for Very Large Models

International audienceWhile Model Driven Engineering is gaining more industrial interest , scalability issues when managing large models have become a major problem in current modeling frameworks. In particular, 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 tackle these issues. However , existing solutions often rely on a single data store, which suits for a specific modeling activity, but may not be optimized for other scenarios. Furthermore, existing solutions often rely on low-level model handling API, limiting NoSQL query performance benefits. In this article, we first introduce NEOEMF, a multi-database model persistence framework able to store very large models in an efficient way according to specific modeling activities. Then, we present the MOGWA¨IMOGWA¨I query framework, able to compute complex OCL queries over very large models in an efficient way with a small memory footprint. All the presented work is fully open source and available online