Evaluation of Contemporary Graph Databases for Efficient Persistence of Large-Scale Models

Scalability in Model-Driven Engineering (MDE) is often a bottleneck for industrial applications. Industrial scale models need to be persisted in a way that allows for their seamless and efficient manipulation, often by multiple stakeholders simultaneously. This paper compares the conventional and commonly used persistence mechanisms in MDE with novel approaches such as the use of graph-based NoSQL databases; Prototype integrations of Neo4J and OrientDB with EMF are used to compare with relational database, XMI and document-based NoSQL database persistence mechanisms. It also compares and benchmarks two approaches for querying models persisted in graph databases to measure and compare their relative performance in terms of memory usage and execution time.