Method GRAPHMIGR8 for migrating relational data to the NEO4J graph model

Authors

DOI:

https://doi.org/10.30837/2522-9818.2025.3.045

Keywords:

database; graph model; migration method; relational model; DBMS; Neo4j.

Abstract

In the modern world of data processing, graph databases are becoming increasingly relevant, allowing for efficient modeling and processing of complex relationships between entities in subject domains. Today, relational databases remain the foundation of most existing software systems. However, relational databases are not always the best solution for software systems that face stringent requirements for scalability and high data availability. In the direction of improving the performance of such systems, decisions regarding migration of their relational databases to NoSQL, particularly to graph databases, are increasingly being made in practice. The subject matter of the article is methods for migrating structured data from the relational database model to the graph model. The goal of the work is to improve the efficiency of migrating relational databases to graph databases by developing a productive method of migration adapted for the Neo4j database management system and providing recommendations for the effective use of migration methods to graph databases. The work addresses the following tasks: development of logical models for relational and graph databases Neo4j in various subject areas for conducting experiments on migration based on them; development of a method for migrating relational data to the Neo4j graph model; planning and conducting experimental research on the effectiveness of the proposed method compared to other migration methods, and development of recommendations regarding the peculiarities of their use. The following methods are used: database design methods; migration methods to graph databases; methods for experimental evaluation of database performance; development methods based on MS SQL Server 18 and Neo4j 5.26 database management systems, Visual Studio 2022 development environment. The following results were obtained: the GraphMigr8 method for migrating relational data to the Neo4j graph model was proposed; experimental evaluation of the quality of migration methods according to performance metrics and semantic data integrity was conducted; recommendations for using migration methods were formed. Conclusions: strengths and weaknesses of existing methods for migrating relational data to the graph data model were identified, the GraphMigr8 method for migrating relational databases to the Neo4j graph model was proposed, which showed better performance and higher semantic correspondence of transformed data.

Author Biographies

Dmytro Mykhnevych, Kharkiv National University of Radio Electronics

Master of Specialty Software Engineering

Oksana Mazurova, Kharkiv National University of Radio Electronics

PhD (Engineering Sciences), Associate Professor,  Associate Professor at the Department of Software Engineering

Oleg Perepichai, Kharkiv National University of Radio Electronics

Graduate Student of Specialty Software Engineering

References

Список літератури

Vyawahare H. Exploring the Hybrid Approach: Integrating Relational and Graph Databases for Enhanced Data Management. Communications in Computer and Information Science. 2024. Vol. 2235, P. 176–191. DOI: https://doi.org/10.1007/978-3-031-74701-4_13

Yedilkhan D., Mukasheva A., Bissengaliyeva D. Performance Analysis of Scaling NoSQL vs SQL: A Comparative Study of MongoDB, Cassandra, and PostgreSQL. IEEE International Conference on Smart Information Systems and Technologies (SIST). 2023. P. 479–483. DOI: https://doi.org/10.1109/SIST58284.2023.10223568

Ragunathan A., Bhavani K., Sasi A. Integration of NoSQL and Relational Databases for Efficient Data Management in Hybrid Cloud Architectures. Journal of Machine and Computing. 2025. P. 1277–1287. DOI: https://doi.org/10.53759/7669/jmc202505100

Kuzochkina A., Shirokopetleva M., Dudar Z. Analyzing and Comparison of NoSQL DBMS. International Scientific-Practical Conference Problems of Infocommunications. Science and Technology (PIC S&T). 2018. Р. 560–564. DOI: https://doi.org/10.1109/INFOCOMMST.2018.8632133

Mhedhbi A., Deshpande A., Salihoğlu S. Modern Techniques for Querying Graph-structured Databases. Foundations and Trends® in Databases. 2024. №14(2). P. 72–185. DOI: https://doi.org/10.1561/1900000090

DB-Engines Ranking. URL: https://db-engines.com/en/ranking (дата звернення: 25.12.2024)

Vicknair C., Macias M., Zhao Z. A comparison of a graph database and a relational database: a data provenance perspective. Proceedings of the 48th Annual Southeast Regional Conference, ACM. 2010. Р.1–6. DOI: https://doi.org/10.1145/1900008.1900067

Bonifati A., Özsu M. T., Tian Y. The Future of Graph Analytics. Companion of the 2024 International Conference on Management of Data (SIGMOD '24). 2024. Р. 544–545. DOI: https://doi.org/10.1145/3626246.3658369

Neo4j, Inc. How to create a graph data model. URL: https://neo4j.com/docs/model/ (дата звернення: 01.04.2025)

De Virgilio R., Maccioni A., Torlone R. Model-driven design of graph databases. International Conference on Conceptual Modeling, Springer. 2024. Р.172-185. DOI: https://doi.org/10.1007/978-3-319-12206-9_14

Ünal Y., Oğuztüzün H. Migration of Data from Relational Database to Graph Database. Proceedings of the 2018 International Conference on Information Systems and Computer Science. 2018. Р. 1–5. DOI: https://doi.org/10.1145/3200842.3200852

Mazurova O., Syvolovskyi I., Syvolovska O. NOSQL database logic design methods for MONGODB and NEO4J. Innovative technologies and scientific solutions for industries. 2022. № 2 (20). С. 52–63. DOI: https://doi.org/10.30837/ITSSI.2022.20.052

Nan Z., Bai X. The study on data migration from relational database to graph database. Journal of Physics: Conference Series. 2019. №1345(2), Р. 022061. DOI: https://doi.org/10.1088/1742-6596/1345/2/022061

Zhao Z., Liu W., French T. Rel2Graph: Automated Mapping From Relational Databases to a Unified Property Knowledge Graph. Research Square [Preprint]. 2024. DOI: https://doi.org/10.21203/rs.3.rs-5451592/v1

Pokorný J. Graph Databases: Their Power and Limitations. IFIP International Conference on Computer Information Systems and Industrial Management. 2015. Р. 58–69. DOI: https://doi.org/10.1007/978-3-319-24369-6_5

Jouili S., Vansteenberghe V. An empirical comparison of graph databases. Proceedings of the 2013 International Conference on Social Computing, IEEE. 2013. Р.708–715. DOI: https://doi.org/10.1109/SocialCom.2013.106

Neo4j, Inc. The Neo4j Cypher Manual. URL: https://neo4j.com/docs/cypher-manual/current/ (дата звернення: 08.04.2025).

References

Vyawahare, H. (2024), “Exploring the Hybrid Approach: Integrating Relational and Graph Databases for Enhanced Data Management”, Communications in Computer and Information Science, No. 2235, Р. 176–191. DOI: https://doi.org/10.1007/978-3-031-74701-4_13

Yedilkhan, D., Mukasheva, A., Bissengaliyeva, D. and Suynullayev, Y. (2023), “Performance Analysis of Scaling NoSQL vs SQL: A Comparative Study of MongoDB, Cassandra, and PostgreSQL”, IEEE International Conference on Smart Information Systems and Technologies (SIST), P. 479–483. DOI: https://doi.org/10.1109/SIST58284.2023.10223568

Ragunathan, A., Bhavani, K., Sasi, A. and Kumar, S. R. (2025), “Integration of NoSQL and Relational Databases for Efficient Data Management in Hybrid Cloud Architectures”, Journal of Machine and Computing, P. 1277–1287. DOI: https://doi.org/10.53759/7669/jmc202505100

Kuzochkina, A., Shirokopetleva, M., Dudar, Z., (2018), “Analyzing and Comparison of NoSQL DBMS“, International Scientific-Practical Conference Problems of Infocommunications. Science and Technology (PIC S&T), Р. 560–564. DOI: https://doi.org/10.1109/INFOCOMMST.2018.8632133

Mhedhbi, A., Deshpande, A. and Salihoğlu, S. (2024), “Modern Techniques for Querying Graph-structured Databases”, Foundations and Trends® in Databases, No.14(2), P. 72–185. DOI: https://doi.org/10.1561/1900000090

DB-Engines Ranking, available at: https://db-engines.com/en/ranking (last accessed 25.12.2024)

Vicknair, C., Macias, M., Zhao, Z., Nan, X., Chen, Y. and Wilkins, D. (2010), “A comparison of a graph database and a relational database: a data provenance perspective”, Proceedings of the 48th Annual Southeast Regional Conference, ACM, P.1–6. DOI: https://doi.org/10.1145/1900008.1900067

Bonifati, A., Özsu, M. T., Tian, Y., Voigt, H., Yu, W. and Zhang, W. (2024), “The Future of Graph Analytics”, Companion of the 2024 International Conference on Management of Data (SIGMOD '24), P. 544–545. DOI: https://doi.org/10.1145/3626246.3658369

Neo4j, Inc. How to create a graph data model, available at: https://neo4j.com/docs/model/ (last accessed 01.04.2025).

De Virgilio, R., Maccioni, A. and Torlone, R. (2014), “Model-driven design of graph databases”, International Conference on Conceptual Modeling, Springer, P.172–185. DOI: https://doi.org/10.1007/978-3-319-12206-9_14

Ünal, Y. and Oğuztüzün, H. (2018), “Migration of Data from Relational Database to Graph Database”, Proceedings of the 2018 International Conference on Information Systems and Computer Science, P. 1–5. DOI: https://doi.org/10.1145/3200842.3200852

Mazurova, O., Syvolovskyi, I. and Syvolovska, O. (2022), “NOSQL database logic design methods for MONGODB and NEO4J”, Innovative technologies and scientific solutions for industries, No. 2(20), Р. 52–63. DOI: https://doi.org/10.30837/ITSSI.2022.20.052

Nan, Z. and Bai, X. (2019), “The study on data migration from relational database to graph database”, Journal of Physics: Conference Series, No. 1345(2), Р. 022061. DOI: https://doi.org/10.1088/1742-6596/1345/2/022061

Zhao, Z., Liu, W. and French, T. (2024), “Rel2Graph: Automated Mapping From Relational Databases to a Unified Property Knowledge Graph”, Research Square [Preprint]. DOI: https://doi.org/10.21203/rs.3.rs-5451592/v1

Pokorný, J. (2015), “Graph Databases: Their Power and Limitations”, IFIP International Conference on Computer Information Systems and Industrial Management, P. 58–69. DOI: https://doi.org/10.1007/978-3-319-24369-6_5

Jouili, S. and Vansteenberghe, V. (2013), “An empirical comparison of graph databases”, Proceedings of the 2013 International Conference on Social Computing, IEEE, P.708–715. DOI: https://doi.org/10.1109/SocialCom.2013.106

Neo4j, Inc. The Neo4j Cypher Manual, available at: https://neo4j.com/docs/cypher-manual/current/ (last accessed 08.04.2025).

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Published

2025-09-25

How to Cite

Mykhnevych, D., Mazurova, O., & Perepichai, O. (2025). Method GRAPHMIGR8 for migrating relational data to the NEO4J graph model. INNOVATIVE TECHNOLOGIES AND SCIENTIFIC SOLUTIONS FOR INDUSTRIES, (3(33), 45–57. https://doi.org/10.30837/2522-9818.2025.3.045

Issue

No. 3(33) (2025): Innovative Technologies and Scientific Solutions for Industries

Section

INFORMATION TECHNOLOGY

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