Abstract
Graph database management systems are widely used in scenarios where the data are intensively connected. Handling such connected data in a relational database is not an efficient task. Converting relational databases to graph ones is one of the solutions that can empower users with handling such data using the graph model features. In this paper, we propose a new algorithm to ease such conversion and overcome the limitations of the existing algorithms. The state of the art algorithms cannot handle multiple relationships types such as unary relationships and associative entities with non-foreign key attributes. Our proposed algorithm, FD2G, leverages the existence of functional dependencies information inside the input relational database to automatically perform the conversion to property graph databases. In addition, we updated the state of the art algorithm, named R2G, to handle its limitations and be able to fairly compare both algorithms performance. We evaluated FD2G against the updated R2G algorithm where it efficiently and effectively outperformed the existing one.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
De Virgilio, R., Maccioni, A., Torlone, R.: Converting relational to graph databases. In: Proceedings of the First International Workshop on Graph Data Management Experience and Systems, New York, NY, USA, pp. 1–6, June 2013. https://doi.org/10.1145/2484425.2484426
De Virgilio, R., Maccioni, A., Torlone, R.: R2G: a tool for migrating relations to graphs. In: Proceeding of the 17th International Conference on Extending Database Technology, EDBT/ICDT 2014 Joint Conference, Athens, Greece, pp. 640–643, March 2014. https://doi.org/10.5441/002/edbt.2014.63
Gupta, M., Rani Aggarwal, R.: Transforming relational database to graph database using Neo4j. In: Proceedings of the Second International Conference on Emerging Research in Computing, Information, Communication and Applications, Bangalore, India, pp. 322–331. ELSEVIER Publications (2014)
Downloading sample databases – North Wind database. https://docs.microsoft.com/en-us/dotnet/framework/data/adonet/sql/linq/downloading-sample-databases. Accessed 27 Mar 2018
Coffman, J., Weaver, A.C.: A framework for evaluating database keyword search strategies. In: Proceedings of the 19th ACM International Conference on Information and Knowledge Management, CIKM 2010, Toronto, Ontario, Canada, pp. 729–738, October 2010. https://doi.org/10.1145/1871437.1871531
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer Nature Switzerland AG
About this paper
Cite this paper
Megid, Y.A., El-Tazi, N., Fahmy, A. (2018). Using Functional Dependencies in Conversion of Relational Databases to Graph Databases. In: Hartmann, S., Ma, H., Hameurlain, A., Pernul, G., Wagner, R. (eds) Database and Expert Systems Applications. DEXA 2018. Lecture Notes in Computer Science(), vol 11030. Springer, Cham. https://doi.org/10.1007/978-3-319-98812-2_31
Download citation
DOI: https://doi.org/10.1007/978-3-319-98812-2_31
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-98811-5
Online ISBN: 978-3-319-98812-2
eBook Packages: Computer ScienceComputer Science (R0)