Incremental extraction of a NoSQL database model using an MDA-based process
This addresses the need for precise model knowledge in NoSQL systems for developers and data engineers, but it is incremental as it builds on existing MDA frameworks.
The paper tackles the problem of querying schema-less NoSQL databases by proposing an incremental process to extract the database model using Model Driven Architecture (MDA) and QVT transformation rules from executed queries, with experimentation on a medical application.
In recent years, the need to use NoSQL systems to store and exploit big data has been steadily increasing. Most of these systems are characterized by the property "schema less" which means absence of the data model when creating a database. This property brings an undeniable flexibility by allowing the evolution of the model during the exploitation of the base. However, the expression of queries requires a precise knowledge of this model. In this paper, we propose an incremental process to extract the model while operating the document-oriented NoSQL database. To do this, we use the Model Driven Architecture (MDA) that provides a formal framework for automatic model transformation. From the insert, delete and update queries executed on the database, we propose formal transformation rules with QVT to generate the physical model of the NoSQL database. An experimentation of the extraction process was performed on a medical application.