Abstract
One of the greatest challenges in big data management is the “Variety” of the data. The data may be presented in various types and formats: structured, semi-structured and unstructured. For instance, data can be modeled as relational, key-value, and graph models. Having a single data platform for managing both well-structured data and NoSQL data is beneficial to users; this approach reduces significantly integration, migration, development, maintenance, and operational issues. Therefore, a challenging research work is how to develop an efficient consolidated single data management platform covering both NoSQL and relational data to reduce integration issues, simplify operations, and eliminate migration issues. In this paper, we envision novel principles and technologies to handle multiple models of data in one unified database system, including model-agnostic storage, unified query processing and indexes, in-memory structures and multi-model transactions. We discuss our visions as well as present research challenges that we need to address.
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Acknowledgment
Contact email: Jiaheng.Lu@helsinki.fi. This work is partially supported by Academy of Finland (Project No. 310321).
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Lu, J., Liu, Z.H., Xu, P., Zhang, C. (2018). UDBMS: Road to Unification for Multi-model Data Management. In: Woo, C., Lu, J., Li, Z., Ling, T., Li, G., Lee, M. (eds) Advances in Conceptual Modeling. ER 2018. Lecture Notes in Computer Science(), vol 11158. Springer, Cham. https://doi.org/10.1007/978-3-030-01391-2_33
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