Automatic Extraction of a Document-oriented NoSQL Schema

Fatma Abdelhedi, Fatma Abdelhedi, Amal Brahim, Hela Rajhi, Rabah Ferhat, Gilles Zurfluh

2021

Abstract

The NoSQL systems make it possible to manage Databases (DB) verifying the 3Vs: Volume, Variety and Velocity. Most of these systems are characterized by the property schemaless which means absence of the data schema when creating a DB. This property provides undeniable flexibility by allowing the schema to evolve while the DB is in use; however, it is a major obstacle for developers and decision makers. Indeed, the expression of queries (SQL type) requires precise knowledge of this schema. In this article, we provide a process for automatically extracting the schema from a NoSQL document-oriented DB. To do this, we use the MDA (Model Driven Architecture). From a NoSQL DB, we propose transformation rules to generate the schema. An experiment of the extraction process was carried out on a medical application.

Paper Citation

in Harvard Style

Abdelhedi F., Brahim A., Rajhi H., Ferhat R. and Zurfluh G. (2021). Automatic Extraction of a Document-oriented NoSQL Schema. In Proceedings of the 23rd International Conference on Enterprise Information Systems - Volume 1: ICEIS, ISBN 978-989-758-509-8, pages 192-199. DOI: 10.5220/0010433501920199

in Bibtex Style

@conference{iceis21,
author={Fatma Abdelhedi and Amal Brahim and Hela Rajhi and Rabah Ferhat and Gilles Zurfluh},
title={Automatic Extraction of a Document-oriented NoSQL Schema},
booktitle={Proceedings of the 23rd International Conference on Enterprise Information Systems - Volume 1: ICEIS,},
year={2021},
pages={192-199},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010433501920199},
isbn={978-989-758-509-8},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 23rd International Conference on Enterprise Information Systems - Volume 1: ICEIS,
TI - Automatic Extraction of a Document-oriented NoSQL Schema
SN - 978-989-758-509-8
AU - Abdelhedi F.
AU - Brahim A.
AU - Rajhi H.
AU - Ferhat R.
AU - Zurfluh G.
PY - 2021
SP - 192
EP - 199
DO - 10.5220/0010433501920199