2019•Unpublished venueOpen access

Comparison of Querying Performance of Neo4j on Graph and Hyper-graph Data Model

Mert Erdemir, Furkan Göz, Alev Mutlu, Pınar Karagöz

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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.

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What this paper is about

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.

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Available 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.

Key concepts: Graph database, Computer science, Graph, Wait-for graph, Theoretical computer science, Information retrieval, Data mining

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