Abstract
Over time, data growth across technology platforms has become a challenge for relational databases. Therefore, it becomes difficult to store and process massive volumes of data and data where the schema is represented by graphs, such as social networking sites. Graph databases emerged as the solution, wherein entities from the domain of interest are represented by nodes and relationships between them by edges. The main objective of this paper is to find out which of the top three open source graph databases are the most complete and efficient. According to DB-Engines Ranking, the top three graph databases are: JanusGraph, Neo4j, and TigerGraph. We apply the OSSpal methodology, which consists of an evaluation based on qualitative and quantitative measures to these databases. The evaluation categories of the OSSpal methodology are focused on software functionalities, attributes and features, available documentation, support and service, user community, and graph database development.
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References
Chen, M., Poulsen, S., Alkhabaz, R., Alawini, A.: A quantitative analysis of student solutions to graph database problems. In: Annual Conference on Innovation and Technology in Computer Science Education, ITiCSE, June 2021, pp. 283–289
Elmasri, R., Navathe, S.B.: Database systems seventh edition
Guia, J., Soares, V.G., Bernardino, J.: Graph databases: Neo4j Analysis. In: ICEIS 2017 - Proceedings of the 19th Int. Conference on Enterprise Information Systems, 2017, vol. 1, pp. 351–356
Ferreira, T., Pedrosa, I., Bernardino, J.: Evaluating open source business intelligence tools using OSSpal methodology. In: IC3K 2017—International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management, vol. 1, pp. 283–288
Wasserman et al.: Open Source Systems: Towards Robust Practices (2017). http://www.springer.com/series/6102
Diogo, M., Cabral, B., Bernardino, J.: Consistency models of NoSQL databases. Future Internet, vol. 11, no. 2. MDPI AG (2019)
Medhi, S., Baruah, H.: Relational database and graph database: a comparative analysis. J. Process Manage. New Technol. 5(2), 1–9 (2017)
Candel, C.J.F., Sevilla Ruiz, D., García-Molina, J.J.: A unified metamodel for NoSQL and relational databases. Inf. Syst. 104 (2022)
Sharma, C.: Design of formal query languages and schemas for graph databases. Ph.D. Thesis (2021)
Qiao, J.: Intelligent big data framework for the technical design of public management applications in sports. Math. Probl. Eng. 2022, 1–9 (2022)
Reynolds, O., García-Domínguez, A., Bencomo, N.: Cronista: a multi-database automated provenance collection system for runtime-models. Inf. Softw. Technol. 141 (2022)
Falcão, T.A., et al.: Comparative analysis of graph databases for git data. J. Phys: Conf. Ser. 1944(1), 012004 (2021)
JanusGraph: JanusGraph (2022). https://janusgraph.org/
Cambridge Intelligence: Cambridge Intelligence (2022). https://cambridge-intelligence.com/keylines/technology/
Melo, D., Cristina, V., Souza, O.: Implementação e Análise do SGBD NoSQL Neo4j sobre a Orquestração do Kubernetes (2020)
Neo4j: Neo4j (2022). https://neo4j.com/
Deutsch, Y.X., Wu, M., Lee, V.: TigerGraph: A Native MPP Graph Database. White paper (2019). http://arxiv.org/abs/1901.08248
Rusu, F., Huang, Z.: In-depth benchmarking of graph database systems with the linked data benchmark council (LDBC) social network benchmark (SNB) (2019). http://arxiv.org/abs/1907.07405
Deutsch, Y.X., Wu, M., Lee, V.E.: Aggregation support for modern graph analytics in TigerGraph. In: Proceedings of the ACM SIGMOD International Conference on Management of Data, June 2020, pp. 377–392
TigerGraph: TigerGraph (2022). https://www.tigergraph.com/
Cruz, S., Bernardino, J.: Project management tools assessment with OSSPAL. In: Proceedings of IC3K 2019, vol. 2, pp. 390–396
Carvalho, G., Mykolyshyn, S., Cabral, B., Bernardino, J., Pereira, V.: Comparative analysis of data modeling design tools. IEEE Access 10, 3351–3365 (2022)
Marques, J.F., Bernardino, J.: Evaluation of Asana, Odoo, and ProjectLibre Project management tools using the OSSpal methodology. In: Proceedings of IC3K 2019, vol. 2, pp. 397–403
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Monteiro, J., Sá, F., Bernardino, J. (2023). Graph Databases Assessment: JanusGraph, Neo4j, and TigerGraph. In: Mesquita, A., Abreu, A., Carvalho, J.V., de Mello, C.H.P. (eds) Perspectives and Trends in Education and Technology . Smart Innovation, Systems and Technologies, vol 320. Springer, Singapore. https://doi.org/10.1007/978-981-19-6585-2_58
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