RESEARCH OF METHODS TO SUPPORT DATA MIGRATION BETWEEN RELATIONAL AND DOCUMENT DATA STORAGE MODELS
DOI:
https://doi.org/10.30837/ITSSI.2022.20.064Keywords:
database, heterogeneous migration, data model, set theoryAbstract
The subject matter of the article is heterogeneous model-inhomogeneous data migration between relational and document-oriented data storage models, existing strategies and methods to support such migrations, the use of relational algebra and set theory in the context of databases in building a new data migration algorithm. The goal of the work is to consider the features and procedure of data migration, explore methods to support data migration between relational and documentary data models, build a mathematical model and algorithm for data migration. The following methods were used: analysis and comparison of existing approaches to data migration, choice of strategy for further use in compiling the migration algorithm, mathematical modeling of the algorithm of heterogeneous model-inhomogeneous data migration, formalization of the data migration algorithm. The following tasks were solved in the article: consideration of the concept and types of data migration, justification for choosing a document-oriented data model as a target for data migration, analysis of existing literature sources on methods and strategies of heterogeneous model data migration from relational to document-oriented data model, highlighting advantages and disadvantages existing methods, choosing an approach to the formation of the data migration algorithm, compiling and describing a mathematical model of data migration using relational algebra and set theory, presentation of the data migration algorithm, which is based on the focus on data queries. The following results were obtained: the possibilities of relational algebra and set theory in the context of data models and queries are used, as well as in model redesign, the strategy of migration of data models is chosen, which provides relational and document-oriented data models, the algorithm of application of this method is described. Conclusions: because of the work, the main methods of migration support for different data storage models are analyzed, with the help of relational algebra, set theory a mathematical model is built, and an algorithm for transforming a relational data model into a document-oriented data model is taken into account. The obtained algorithm is suitable for use in real examples, and is the subject of further research and possible improvements, analysis of efficiency in comparison with other methods.
References
"International Roadmap for Devices and Systems. More Moore White Paper", available at: https://irds.ieee.org/images/files/pdf/2016_MM.pdf (last accessed: 25.03.2022).
Morris, J. (2012), Practical Data Migration, BCS, The Chartered Institute for IT, London, 266 p.
"Homogeneous vs Heterogeneous migration", available at: https://rtfm.co.ua/aws-database-migration-service-obzor-i-primer-migracii-self-hosted-mariadb-v-aws-aurora-rds/#Homogeneous_vs_Heterogeneous_migration (last accessed: 30.03.2022).
Preston, Z. (2021), Practical Guide to Large Database Migration, CRC Press, USA, 198 p.
Andreas, M. (2015), "Providing Database Migration Tools. A Practitioner’s Approach", 21st International Conference on Very Large Data Bases (VLDB), P. 635 – 641.
Ji, L. F., Azmi, N. F. M. (2020), "The development of a new data migration model for NOSQL databases with different schemas in environment management system", Journal of Environmental Treatment Techniques, No. 8 (2), P. 787–793.
Ceresnak, R., Dudas, A., Matiasko, K. (2021), "Mapping rules for schema transformation : SQL to NoSQL and back", International Conference on Information and Digital Technologies, P. 52–58. DOI: https://doi.org/10.1109/IDT52577.2021.9497629
Hanine, M., Bendarag, A., Boutkhoum, O. (2015), "Data Migration Methodology from Relational to NoSQL Databases", International Journal of Computer, Electrical, Automation, Control and Information, Engineering, No. 9 (12), P. 2566–2570.
Alalfi, M. H. (2018), "Automated Algorithm for Data Migration from Relational to NoSQL Databases", Al-Nahrain Journal for Engineering Sciences (NJES), No. 21 (1), P. 60–65. DOI: https://doi.org/10.29194/NJES2101
Fouad, T., Mohamed, B. (2019), "Model transformation from object relational database to NoSQL document database", NISS19, No. 49, P. 1–5. DOI: https://doi.org/10.1145/3320326.3320381
Li, X., Ma, Z., Chen, H. (2014), "QODM: A Query-Oriented Data Modeling Approach for NoSQL Databases", IEEE Workshop on Advanced Research and Technology in Industry Applications, P. 338–345.
Alotaibi, O., Pardede, E. (2019), "Transformation of Schema from Relational Database (RDB) to NoSQL Databases", Data, No. 4 (4), P. 148. DOI: https://doi.org/10.3390/data4040148
Ain El Hayat, S., Bahaj, M. (2020), "Modeling and transformation from temporal object relational database into mongodb: Rules", Advances in Science, Technology and Engineering Systems, No. 5 (4), P. 618–625. DOI: https://doi.org/10.25046/aj050473
Mason, R. T. (2015), "NoSQL databases and data modeling techniques for a document-oriented NoSQL database", Informing Science & IT Education Conference (InSITE), P. 259–268. DOI: https://doi.org/10.28945/2245
Alekseev, A. A., Osipova, V. V., Ivanov, M. A. (2016), "Efficient data management tools for the heterogeneous big data warehouse", Physics of Particles and Nuclei Letters, No. 13 (5), P. 689–692. DOI: https://doi.org/10.1134/S1547477116050022
Gu, Y., Wang, X., Shen, S., Wang, J., Kim, J.-U. (2015), "Analysis of data storage mechanism in NoSQL database MongoDB", 2015 IEEE International Conference on Consumer Electronics, P. 158–159.
Dabowsa, N. I., Maatuk, A. M., Elakeili, S. M. (2021), "Converting Relational Database to Document-Oriented NoSQL Cloud Database", 2021 IEEE 1st International Maghreb Meeting of the Conference on Sciences and Techniques of Automatic Control and Computer Engineering MI-STA, P. 381–386. DOI: https://doi.org/10.1109/MI-STA52233.2021.9464488
Date, С. J. (2012), SQL and Relational Theory: How to Write Accurate SQL Code, O'Reilly Media, London, 448 p.
Kuzochkina, A., Shirokopetleva, M., Dudar, Z. (2018), "Analyzing and Comparison of NoSQL DBMS", International Scientific-Practical Conference on Problems of Infocommunications Science and Technology, P. 560–564. DOI: https://doi.org/10.1109/INFOCOMMST.2018.8632133 "DB-Engines Ranking", available at: https://db-engines.com/en/ranking (last accessed: 10.04.2022).
Chickerur, S., Goudar, A., Kinnerkar, A. (2015), "Comparison of Relational Database with Document-Oriented Database (MongoDB) for Big Data Applications", 8th International Conference on Advanced Software Engineering & Its Applications (ASEA), P. 41–47. DOI: https://doi.org/10.1109/ASEA.2015.19
Stepovik, A. N, Efanov, N. V. (2019), "Analysis of relational and non-relational databases", Digitization of the economy: directions, methods, tools, P. 414–416.
Downloads
Published
How to Cite
Issue
Section
License
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
Our journal abides by the Creative Commons copyright rights and permissions for open access journals.
Authors who publish with this journal agree to the following terms:
Authors hold the copyright without restrictions and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License (CC BY-NC-SA 4.0) that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal.
Authors are able to enter into separate, additional contractual arrangements for the non-commercial and non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal.
Authors are permitted and encouraged to post their published work online (e.g., in institutional repositories or on their website) as it can lead to productive exchanges, as well as earlier and greater citation of published work.