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Categorical Management of Multi-Model Data

Published:07 September 2021Publication History

ABSTRACT

In this vision paper, we introduce an idea of a framework that would enable us to model, represent, and manage multi-model data in a unified and abstract way. Its core idea exploits constructs provided by category theory, which is sufficiently general but still simple enough to cover any of the logical data models used in contemporary databases. Focusing on promising features and taking into account mature and verified principles, we overview the key parts of the framework and outline open questions and research directions that need to be further investigated. The ultimate objective is to pursue the idea of a self-tuning system that would permit us to collapse the traditionally understood conceptual and logical layers into just a single model allowing for unified handling of schemas, data instances, as well as queries.

References

  1. Suad Alagić and Philip A. Bernstein. 2002. A Model Theory for Generic Schema Management. In Database Programming Languages. Springer, 228–246.Google ScholarGoogle Scholar
  2. Paolo Atzeni, Francesca Bugiotti, Luca Cabibbo, and Riccardo Torlone. 2020. Data Modeling in the NoSQL World. Computer Standards and Interfaces 67 (2020), 103–149.Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. Michael Barr and Charles Wells. 1990. Category Theory for Computing Science. Vol. 49. Prentice Hall New York.Google ScholarGoogle Scholar
  4. Francesco Basciani, Juri Di Rocco, Davide Di Ruscio, Alfonso Pierantonio, and Ludovico Iovino. 2020. TyphonML: A Modeling Environment to Develop Hybrid Polystores. In MODELS ’20 (Virtual Event, Canada). ACM, Article 2, 5 pages. https://doi.org/10.1145/3417990.3421999Google ScholarGoogle Scholar
  5. P.P. Chen. 1976. The Entity-Relationship Model – Toward a Unified View of Data. ACM Transactions on Database Systems 1, 1 (March 1976), 9–36. https://doi.org/10.1145/320434.320440Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. Qingsong Guo, Jiaheng Lu, Chao Zhang, Calvin Sun, and Steven Yuan. 2020. Multi-Model Data Query Languages and Processing Paradigms. In CIKM ’20. ACM, 3505–3506. https://doi.org/10.1145/3340531.3412174Google ScholarGoogle Scholar
  7. Andrea Hillenbrand, Maksym Levchenko, Uta Störl, Stefanie Scherzinger, and Meike Klettke. 2019. MigCast: Putting a Price Tag on Data Model Evolution in NoSQL Data Stores. In SIGMOD ’19(Amsterdam, Netherlands). ACM, 1925–1928. https://doi.org/10.1145/3299869.3320223Google ScholarGoogle Scholar
  8. Jeremy Kepner, Julian Chaidez, Vijay Gadepally, and Hayden Jansen. 2015. Associative Arrays: Unified Mathematics for Spreadsheets, Databases, Matrices, and Graphs. CoRR abs/1501.05709(2015). arXiv:1501.05709Google ScholarGoogle Scholar
  9. Boyan Kolev, Raquel Pau, Oleksandra Levchenko, Patrick Valduriez, Ricardo Jiménez-Peris, and José Orlando Pereira. 2016. Benchmarking polystores: The CloudMdSQL experience. In BigData ’16. 2574–2579.Google ScholarGoogle Scholar
  10. M. Kolonko and S. Müllenbach. 2020. Polyglot Persistence in Conceptual Modeling for Information Analysis. In ACIT ’20. 590–594.Google ScholarGoogle Scholar
  11. Eric Leclercq and Marinette Savonnet. 2019. TDM: A Tensor Data Model for Logical Data Independence in Polystore Systems. In VLDB ’18 Workshops. Springer, 39–56. https://doi.org/10.1007/978-3-030-14177-6_4Google ScholarGoogle ScholarCross RefCross Ref
  12. Lippe, E. and Ter Hofstede, A. H. M.1996. A Category Theory Approach to Conceptual Data Modeling. RAIRO-Theor. Inf. Appl. 30, 1 (1996), 31–79.Google ScholarGoogle ScholarCross RefCross Ref
  13. Zhen Hua Liu, Jiaheng Lu, Dieter Gawlick, Heli Helskyaho, Gregory Pogossiants, and Zhe Wu. 2019. Multi-model Database Management Systems - A Look Forward. In VLDB ’18 Workshops. Springer, 16–29. https://doi.org/10.1007/978-3-030-14177-6_2Google ScholarGoogle Scholar
  14. Jiaheng Lu and Irena Holubová. 2019. Multi-Model Databases: A New Journey to Handle the Variety of Data. ACM Comput. Surv. 52, 3, Article 55 (2019). https://doi.org/10.1145/3323214Google ScholarGoogle Scholar
  15. Jiaheng Lu, Zhen Hua Liu, Pengfei Xu, and Chao Zhang. 2018. UDBMS: Road to Unification for Multi-model Data Management. In ER ’18 Workshops(LNCS, Vol. 11158). Springer, 285–294. https://doi.org/10.1007/978-3-030-01391-2_33Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. Kian Win Ong, Yannis Papakonstantinou, and Romain Vernoux. 2014. The SQL++ Semi-structured Data Model and Query Language: A Capabilities Survey of SQL-on-Hadoop, NoSQL and NewSQL Databases. CoRR abs/1405.3631(2014).Google ScholarGoogle Scholar
  17. Atzeni Paolo, Stefano Ceri, Stefano Paraboschi, and Riccardo Torlone. 1999. Database Systems: Concepts, Languages and Architectures.Google ScholarGoogle Scholar
  18. Marek Polák, Martin Nečaský, and Irena Holubová. 2013. DaemonX: Design, Adaptation, Evolution, and Management of Native XML (and More Other) Formats. In IIWAS ’13 (Vienna, Austria). ACM, 484–493.Google ScholarGoogle Scholar
  19. James Rumbaugh, Ivar Jacobson, and Grady Booch. 2004. Unified modeling language reference manual. Pearson Higher Education.Google ScholarGoogle Scholar
  20. Patrick Schultz, David I. Spivak, Christina Vasilakopoulou, and Ryan Wisnesky. 2017. Algebraic Databases. Theory & Applications of Categories 32, 16-19 (2017), 547 – 619.Google ScholarGoogle Scholar
  21. David I Spivak and Ryan Wisnesky. 2015. Relational Foundations for Functorial Data Migration. In DBPL ’15. ACM, 21–28.Google ScholarGoogle Scholar
  22. Martin Svoboda, Pavel Contos, and Irena Holubova. 2021. Categorical Modeling of Multi-Model Data: One Model to Rule Them All. In MEDI ’21: Proceedings of the 10th International Conference on Model and Data Engineering(LNCS, Vol. 12732). Springer, 1–8. https://doi.org/10.1007/978-3-030-78428-7_15Google ScholarGoogle ScholarDigital LibraryDigital Library
  23. Laurent Thiry, Heng Zhao, and Michel Hassenforder. 2018. Categories for (Big) Data models and optimization. Journal of Big Data 5, 1 (2018), 1–20. https://doi.org/10.1186/s40537-018-0132-9Google ScholarGoogle ScholarCross RefCross Ref
  24. Chris Tuijn and Marc Gyssens. 1996. ”CGOOD, a Categorical Graph-oriented Object Data Model”. Theoretical Computer Science 160, 1-2 (1996), 217–239.Google ScholarGoogle ScholarDigital LibraryDigital Library
  25. Michal Vavrek, Irena Holubová, and Stefanie Scherzinger. 2019. MM-evolver: A Multi-model Evolution Management Tool. In EDBT ’19. OpenProceedings.org, 586–589.Google ScholarGoogle Scholar
  26. Chao Zhang, Jiaheng Lu, Pengfei Xu, and Yuxing Chen. 2018. UniBench: A Benchmark for Multi-model Database Management Systems. In TPCTC ’18(LNCS, Vol. 11135). Springer, 7–23. https://doi.org/10.1007/978-3-030-11404-6_2Google ScholarGoogle Scholar
  1. Categorical Management of Multi-Model Data

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    • Published in

      cover image ACM Other conferences
      IDEAS '21: Proceedings of the 25th International Database Engineering & Applications Symposium
      July 2021
      308 pages
      ISBN:9781450389914
      DOI:10.1145/3472163

      Copyright © 2021 ACM

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      Publication History

      • Published: 7 September 2021

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