A Simplified Systematic Review and Analysis of Studies on Schema Evolution in Polyglot Persistence Applications
Abstract
The evolution of schemas in polyglot persistence projects is described in the literature as a research gap due to the challenges posed by the different data models used and the concern of maintaining data integrity and consistency after changes. This study presents a simplified systematic literature review, highlighting technological advancements aimed at simplifying schema evolution in modern and complex systems while also emphasizing the scientific relevance of the issue, confirming the scarcity of specific studies on schema evolution in polyglot persistence applications. Works addressing different database architectures (hybrid, multimodel, polystore) and data models (relational, document, and graph) are analyzed. A comparative analysis of the studies reveals that strategies for schema evolution in polyglot architecthures make use of unified data model abstractions, with operations embedded in proprietary languages or systems.References
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Gobert, M. (2020). Supporting Schema Evolution in Hybrid Database Systems. In Proceedings of the VLDB 2020 PhD Workshop. VLDB Endowment. Copyright (C) 2020 for this paper by its authors. Copying permitted for private and academic purposes.
Hausler, D. (2024). Estimation, Impact and Visualization of Schema Evolution in Graph Databases. In Proceedings of the ACM/IEEE 27th International Conference on Model Driven Engineering Languages and Systems, pages 123–129.
Kitchenham, B. (2004). Procedures for Performing Systematic Reviews. Keele, UK, Keele University, 33(2004):1–26.
Kosmerl, I., Rabuzin, K., and Šestak, M. (2020). Multi-Model Databases - Introducing Polyglot Persistence in the Big Data World. International Convention on Information and Communication Technology, Electronics and Microelectronics, pages 1724 – 1729.
Lajam, O. and Mohammed, S. (2022). Revisiting Polyglot Persistence: From Principles to Practice. International Journal of Advanced Computer Science and Applications, 13(5).
Lu, J. and Holubová, I. (2019). Multi-model databases: A New Journey to Handle the Variety of Data. ACM Computing Surveys (CSUR), 52(3):1–38.
Murazzo, M., Gómez, P., Rodríguez, N., and Medel, D. (2019). Database NewSQL Performance Evaluation for Big Data in the Public Cloud. In Cloud Computing and Big Data: 7th Conference, JCC&BD, Revised Selected Papers 7, pages 110–121. Springer.
Sadalage, P. J. and Fowler, M. (2013). NoSQL Distilled: A Brief Guide to the Emerging World of Polyglot Persistence. Pearson Education.
Auge, T. and Heuer, A. (2022). Enhanced Inversion of Schema Evolution with Provenance. arXiv preprint arXiv:2211.13810.
Bártík, J., Koupil, P., and Holubová, I. (2024). Modelling and Evolution Management of Multi-Model Data. In 39th ACM/SIGAPP Symposium on Applied Computing (SAC), page 3. ACM.
Chillón, A. H., Klettke, M., Ruiz, D. S., and Molina, J. G. (2022). A Taxonomy of Schema Changes for NoSQL Databases. arXiv preprint arXiv:2205.11660.
Chillón, A. H., Klettke, M., Ruiz, D. S., and Molina, J. G. (2024). A Generic Schema Evolution Approach for NoSQL and Relational Databases. IEEE Transactions on Knowledge and Data Engineering.
Gessert, F., Wingerath, W., Ritter, N., Gessert, F., Wingerath, W., and Ritter, N. (2020). Polyglot Persistence in Data Management. Fast and Scalable Cloud Data Management, pages 149–174.
Glake, D., Kiehn, F., Schmidt, M., Panse, F., and Ritter, N. (2022). Towards Polyglot Data Stores–Overview and Open Research Questions. arXiv preprint arXiv:2204.05779.
Gobert, M. (2020). Supporting Schema Evolution in Hybrid Database Systems. In Proceedings of the VLDB 2020 PhD Workshop. VLDB Endowment. Copyright (C) 2020 for this paper by its authors. Copying permitted for private and academic purposes.
Hausler, D. (2024). Estimation, Impact and Visualization of Schema Evolution in Graph Databases. In Proceedings of the ACM/IEEE 27th International Conference on Model Driven Engineering Languages and Systems, pages 123–129.
Kitchenham, B. (2004). Procedures for Performing Systematic Reviews. Keele, UK, Keele University, 33(2004):1–26.
Kosmerl, I., Rabuzin, K., and Šestak, M. (2020). Multi-Model Databases - Introducing Polyglot Persistence in the Big Data World. International Convention on Information and Communication Technology, Electronics and Microelectronics, pages 1724 – 1729.
Lajam, O. and Mohammed, S. (2022). Revisiting Polyglot Persistence: From Principles to Practice. International Journal of Advanced Computer Science and Applications, 13(5).
Lu, J. and Holubová, I. (2019). Multi-model databases: A New Journey to Handle the Variety of Data. ACM Computing Surveys (CSUR), 52(3):1–38.
Murazzo, M., Gómez, P., Rodríguez, N., and Medel, D. (2019). Database NewSQL Performance Evaluation for Big Data in the Public Cloud. In Cloud Computing and Big Data: 7th Conference, JCC&BD, Revised Selected Papers 7, pages 110–121. Springer.
Sadalage, P. J. and Fowler, M. (2013). NoSQL Distilled: A Brief Guide to the Emerging World of Polyglot Persistence. Pearson Education.
Published
2025-04-23
How to Cite
ARAUJO, Lilian N.; SILVA, Hudson Afonso Batista da; MELLO, Ronaldo S..
A Simplified Systematic Review and Analysis of Studies on Schema Evolution in Polyglot Persistence Applications. In: REGIONAL DATABASE SCHOOL (ERBD), 20. , 2025, Florianópolis/SC.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2025
.
p. 20-29.
ISSN 2595-413X.
DOI: https://doi.org/10.5753/erbd.2025.7322.
