Runtime Translation of Model-Level Queries to Persistence-Level

Different studies have proved that XMI (default persistence in Eclipse Modelling Framework) has some limitations when operating with large models. Recent approaches propose databases for persistence of models. Therefore, persistence level languages could be used to efficiently query models. While persistence level languages increase performance as they take advantages of underlying databases, they compromise usability for model engineers. Model engineers are familiar with model-level query languages (e.g. EOL or OCL). We present MQT (Model Query Translator), a runtime translation of model-level to persistence-level queries. Thus, we provide model engineers the usability of a model level language but also take advantage of performance optimization of databases. We have performed an empirical study of the approach using the GraBaTs 2009 case study (models from 8.8 MB to 646 MB) and results indicate that persisting models in a database, and combining it with runtime query translation provides a promising alternative for querying large models.