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Conference object . 2020
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Croatian Scientific Bibliography - CROSBI
Conference object . 2020
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https://doi.org/10.31410/itema...
Article . 2020 . Peer-reviewed
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GRAPH DATABASE MANAGEMENT SYSTEMS AND GRAPH THEORY

descriptionPublicationkeyboard_double_arrow_right Article , Conference object , Other literature type 01 Jan 2020 Croatia Publisher:Association of Economists and Managers of the Balkans, Belgrade, SerbiaJournal:Fourth International Scientific Conference ITEMA Recent Advances in Information Technology, Tourism, Economics, Management and Agriculture (issn: 2683-5991, Copyright policy )
Authors: Kornelije Rabuzin; Sonja Ristić; Robert Kudelić;

doi: 10.31410/itema.2020.39

GRAPH DATABASE MANAGEMENT SYSTEMS AND GRAPH THEORY

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.

Country
Croatia
Related Organizations
Keywords

MS SQL server, Neo4j ; MS SQL server ; Oracle ; Cypher, Neo4j, Oracle, Cypher

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    influence
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green
hybrid