Abstract
The existence of the variety of data models and their associated data processing technologies make data management extremely complex. In this paper, we envision a single Multi-Model DataBase Management Systems (MMDBMS) providing declarative accesses to a variety of data models. We briefly review the history of the evolution of the DBMS technology to derive requirements of MMDBMSs and then we illustrate our ideas of building MMDBMSs satisfying those requirements. Since the relational algebra is not powerful enough to provide a mathematical foundation for MMDBMSs, we promote the category theory as a new theoretical foundation, which is a generalization of the set theory. We also suggest a set of shared data infrastructure services among data models to support “Just-In-Time” multi-model data access autonomously.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Spoth, W., et al.: Adaptive schema databases. In: CIDR (2017)
Liu, Z.H., Gawlick, D.: Management of flexible schema data in RDBMSs-opportunities and limitations for NoSQL. In: CIDR (2015)
Lahiri, T., et al.: Oracle database in-memory: a dual format in-memory database. In: Data Engineering (ICDE) (2015)
Gawlick, D., Chan, E.S., Ghoneimy, A., Liu, Z.H.: Mastering situation awareness: the next big challenge? ACM SIGMOD Rec. 44(3), 19–24 (2015)
Spivak, D.I.: Database queries and constraints via lifting problems. Math. Struct. Comput. Sci. 24(6) (2014)
Grosvenor, M.P., Clement, A., Hand, S.: Musketeer: all for one, one for all in data processing systems. In: EuroSys, pp. 1–16 (2015)
Lim, H., Han, Y., Babu, S.: How to fit when no one size fits. In: CIDR (2013)
Elmore, A., et al.: A demonstration of the BigDAWG polystore system. Proc. VLDB Endow. 8(12), 1908–1911 (2015)
Schultz, P., et al.: Algebraic databases. CoRR abs/1602.03501 (2016)
Fleming, M., Gunther, R., Rosebrugh, R.: A database of categories. J. Symb. Comput. 35, 127–135 (2002)
Wisnesky, R., Spivak, D.: A functorial query language. Presented at Boston Haskell (2014). http://categoricaldata.net/fql/haskell.pdf
Abiteboul, S., et al.: Research directions for principles of data management (Abridged). SIGMOD Rec. 45(4), 5–17 (2016)
Liu, Z.H., et al.: Towards a physical XML independent XQuery/SQL/XML engine. PVLDB 1(2), 1356–1367 (2008)
Michael, B., Charles, W.: Category Theory for Computing Science. Reprints in Theory and Applications of Categories, vol. 22 (2012)
Yan, Da, et al.: Big graph analytics platforms. Found. Trends Databases 7(1–2), 1–195 (2017)
Lu, J., Holubová, I.: Multi-model data management: what’s new and what’s next? In: EDBT 2017, pp. 602–605 (2017)
World Wide Web Consortium (W3C). https://www.w3.org/
Wisnesky, R., Spivak, D.I., Schultz, P., Subrahmanian, E.: Functorial data migration: from theory to practice. CoRR abs/1502.05947 (2015)
Riehl, E.: Category Theory in Context. Courier Dover Publications, Mineola (2017)
Toman, D., Weddell, G.E.: Fundamentals of Physical Design and Query Compilation. Synthesis Lectures on Data Management. Morgan & Claypool Publishers, San Rafael (2011)
Atzeni, P., Torlone, R.: A metamodel approach for the management of multiple models and translation of schemes. Inf. Syst. 18(6), 349–362 (1993)
Property Graph Query Language 1.1 Specification. http://pgql-lang.org/spec/1.1/
Liu, Z.H., Hammerschmidt, B.C., McMahon, D., Liu, Y., Chang, H.J.: Closing the functional and performance gap between SQL and NoSQL. In: SIGMOD Conference 2016, pp. 227–238 (2016)
Girard, J.-Y.: Locus solum: from the rules of logic to logic of rules. Math. Struct. Comput. Sci. 11(3), 301–506 (2001)
Girard, J.-Y.: From foundations to ludics. Bull. Symb. Log. 9(2), 131–168 (2003)
Lecomte, A.: Meaning, Logic and Ludics. Imperial College Press, London (2011)
Liu, Y., et al.: ProbeSim: scalable single-source and top-k SimRank computations on dynamic graphs. PVLDB 11(1), 14–26 (2017)
Lu, J.: Towards benchmarking multi-model databases. In: CIDR (2017)
Chen, J., et al.: Big data challenge: a data management perspective. Front. Comput. Sci. 7(2), 157–164 (2013)
Acknowledgement
Jiaheng Lu is partially supported by the Academy of Finland (No. 310321).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Switzerland AG
About this paper
Cite this paper
Liu, Z.H., Lu, J., Gawlick, D., Helskyaho, H., Pogossiants, G., Wu, Z. (2019). Multi-model Database Management Systems - A Look Forward. In: Gadepally, V., Mattson, T., Stonebraker, M., Wang, F., Luo, G., Teodoro, G. (eds) Heterogeneous Data Management, Polystores, and Analytics for Healthcare. DMAH Poly 2018 2018. Lecture Notes in Computer Science(), vol 11470. Springer, Cham. https://doi.org/10.1007/978-3-030-14177-6_2
Download citation
DOI: https://doi.org/10.1007/978-3-030-14177-6_2
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-14176-9
Online ISBN: 978-3-030-14177-6
eBook Packages: Computer ScienceComputer Science (R0)