Kornelije Rabuzin – University of Zagreb, Faculty of organization and informatics, Pavlinska 2, Varaždin, Croatia
Sonja Ristić – University of Novi Sad, Faculty of technical sciences, Trg D. Obradovića 6, Novi Sad, Serbia
Robert Kudelić – University of Zagreb, Faculty of organization and informatics, Pavlinska 2, Varaždin, Croatia
DOI: https://doi.org/10.31410/ITEMA.2020.39
4th International Scientific Conference on Recent Advances in Information Technology, Tourism, Economics, Management and Agriculture – ITEMA 2020, Online/virtual, October 8, 2020, CONFERENCE PROCEEDINGS published by the Association of Economists and Managers of the Balkans, Belgrade; Printed by: SKRIPTA International, Belgrade, ISBN 978-86-80194-36-3, ISSN 2683-5991, DOI: https://doi.org/10.31410/ITEMA.2020
Abstract
In recent years, graph databases have become far more important. They have been proven to be an excellent choice for storing and managing large amounts of interconnected data. Since graph databases (GDB) rely on a graph data model based on graph theory, this study examines whether currently available graph database management systems support the principles of graph theory, and, if so, to what extent. We also show how these systems differ in terms of implementation and languages, and we also discuss which graph database management systems are used today and why.
Keywords
Neo4j, MS SQL server, Oracle, Cypher.
References
Chen, J., Song, Q., Zhao, C., & Li, Z. (2020). Graph database and relational database performance comparison on a transportation network doi:10.1007/978-981-15-6634-9_37
Gupta, S., Pal, S., & Chakraborty, M. (2020). A study on various database models: Relational, graph, and hybrid databases doi:10.1007/978-981-15-0361-0_11
He, H., & Singh, A. K., (2008). Graphs-at-a-time: query language and access methods for graph databases. In Proceedings of the 2008 ACM SIGMOD international conference on Management of data (pp. 405–418).
Holzschuher, F., & Peinl, R., (2013). Performance of graph query languages: comparison of cypher, gremlin and native access in Neo4j. In Proceedings of the Joint EDBT/ICDT 2013 Workshops (pp. 195–204).
Kudelić, R., (2016). Monte-Carlo randomized algorithm for minimal feedback arc set problem. Applied soft computing, 235 – 246. https://doi.org/10.1016/j.asoc.2015.12.018
Maleković, M., Rabuzin, K., & Šestak, M., (2016). Graph Databases-are they really so new. International Journal of Advances in Science Engineering and Technology. 4 (2016). Retrieved from http://bib.irb.hr/prikazi-rad?rad=843723
Rabuzin, K., Konecki, M., & Šestak, M., 2016a. Implementing CHECK Integrity Constraint in Graph Databases. Proceedings of the 82nd IIER International Conference. Retrieved from http://bib.irb.hr/prikazi-rad?rad=836861
Rabuzin, K., Maleković, M., & Šestak, M. (2016). Gremlin By Example. International Conference on Advances in Big Data Analytics, 144–149.
Rabuzin, K., Šestak, M., & Konecki, M., 2016b. Implementing UNIQUE Integrity Constraint in Graph Databases. Multi-Conference on Computing in the Global Information Technology. Retrieved from http://bib.irb.hr/prikazi-rad?rad=844504
Robinson, I., Webber, J., & Eifrem, E., 2013. Graph Databases. Information Management. https://doi.org/http://dx.doi.org/10.1016/B978-0-12-407192-6.00003-0
Wilson, J. R., 1996. Graph Theory. UK: Addison Wesley.