Incremental extraction of a NoSQL database model using an MDA-based process

TL;DR

This paper presents an incremental method using Model Driven Architecture to extract and formalize the data model from a schema-less NoSQL database during its operation, facilitating query understanding and management.

Contribution

It introduces a novel MDA-based process for extracting NoSQL data models dynamically from database operations, enabling better schema comprehension.

Findings

Successful extraction of the data model from a medical NoSQL database

Formal transformation rules effectively generate the physical model

Process supports evolving schema during database use

Abstract

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.