Experimental Evaluation of Graph Databases: JanusGraph, Nebula Graph, Neo4j, and TigerGraph
Source abstract
Abstract
NoSQL databases were created with the primary goal of addressing the shortcomings in the efficiency of relational databases, and can be of four types: document, column, key-value, and graph databases. Graph databases can store data and relationships efficiently, and have a flexible and easy-to-understand data schema. In this paper, we perform an experimental evaluation of the four most popular graph databases: JanusGraph, Nebula Graph, Neo4j, and TigerGraph. Database performance is evaluated using the Linked Data Benchmark Council’s Social Network Benchmark (LDBC SNB). In the experiments, we analyze the execution time of the queries, the loading time of the nodes and the RAM and CPU usage for each database. In our analysis, Neo4j was the graph database with the best performance across all metrics.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Graph Theory and Algorithms · Distributed and Parallel Computing Systems · Interconnection Networks and Systems
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Polytechnic of Coimbra, Coimbra Institute of Engineering (ISEC), Rua Pedro Nunes, 3030-199 Coimbra, Portugal
Centre for Informatics and Systems of the University of Coimbra (CISUC), Pólo II, Pinhal de Marrocos, 3030-290 Coimbra, Portugal
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