NoSQL Data Models

Trends and Challenges

Volume 1 – Databases and Big Data SET Coordinated by Dominique Laurent and Anne Laurent

NoSQL Data Models

Edited by

Olivier Pivert, University of Rennes, France

ISBN : 9781786303646

Publication Date : July 2018

Hardcover 278 pp

145.00 USD



The topic of NoSQL databases has emerged recently in the face of the challenge regarding Big Data – namely, the ever-increasing volume of data to be handled. It is now recognized that relational databases are not appropriate in this context, and thus new database models and techniques are necessary.

This book presents recent studies in the field, covering the following basic areas: semantic data management, graph databases and Big Data management in Cloud environments. The authors report on research regarding the evolution of basic concepts such as data models, query languages and new challenges related to issues of implementation.


1. NoSQL Languages and Systems, Kim Nguyen.
2. Distributed SPARQL Query Processing: a Case Study with Apache Spark, Bernd Amann, Olivier Curé and Hubert Naacke.
3. Doing Web Data: from Dataset Recommendation to Data Linking, Manel Achichi, Mohamed Ben Ellefi, Zohra Bellahsene and Konstantin Todorov.
4. Big Data Integration in Cloud Environments: Requirements, Solutions and Challenges, Rami Sellami and Bruno Defude.
5. Querying RDF Data: a Multigraph-based Approach, Vijay Ingalalli, Dino Ienco and Pascal Poncelet.
6. Fuzzy Preference Queries to NoSQL Graph Databases, Arnaud Castelltort, Anne Laurent, Olivier Pivert, Olfa Slama and Virginie Thion.
7. Relevant Filtering in a Distributed Content-based Publish/Subscribe System, Cédric du Mouza and Nicolas Travers.

About the authors

Olivier Pivert is Full Professor of Computer Science at the École Nationale Supérieure des Sciences Appliquées et de Technologie (University of Rennes, France), and a member of the Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), where he leads the research team Shaman. He has published over 300 papers on database-related topics.