Authors:
Mert Erdemir
1
;
Furkan Goz
2
;
Alev Mutlu
2
and
Pinar Karagoz
1
Affiliations:
1
Department of Computer Engineering, Middle East Technical University, Ankara and Turkey
;
2
Department of Computer Engineering, Kocaeli University, Kocaeli and Turkey
Keyword(s):
Graph Database, Graph, Hyper-graph, Performance Analysis, Neo4j.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Business Analytics
;
Data Analytics
;
Data Engineering
;
Knowledge Discovery and Information Retrieval
;
Knowledge-Based Systems
;
Structured Data Analysis and Statistical Methods
;
Symbolic Systems
Abstract:
Graph databases are gaining wide use as they provide flexible mechanisms to model real world entities and the relationships among them. In the literature, there exists several studies that evaluate performance of graph databases and graph database query languages. However, there is limited work on comparing performance for graph database querying under different graph representation models. In this study, we focus on two graph representation models: ordinary graphs vs. hyper-graphs, and investigate the querying performance of Neo4j for various query types under each model. The analysis conducted on a benchmark data set reveal what type of queries perform better on each representation.