Multi-Model Data Query Languages and Processing Paradigms

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Abstract

Specifying users' interests with a formal query language is a typically challenging task, which becomes even harder in the context of multi-model data management because we have to deal with data variety. It usually lacks a unified schema to help the users issuing their queries, or has an incomplete schema as data come from disparate sources. Multi-Model DataBases (MMDBs) have emerged as a promising approach for dealing with this task as they are capable of accommodating and querying the multi-model data in a single system. This tutorial aims to offer a comprehensive presentation of a wide range of query languages for MMDBs and to make comparisons of their properties from multiple perspectives. We will discuss the essence of cross-model query processing and provide insights on the research challenges and directions for future work. The tutorial will also offer the participants hands-on experience in applying MMDBs to issue multi-model data queries.

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Guo, Q., Lu, J., Zhang, C., Sun, C., & Yuan, S. (2020). Multi-Model Data Query Languages and Processing Paradigms. In International Conference on Information and Knowledge Management, Proceedings (pp. 3505–3506). Association for Computing Machinery. https://doi.org/10.1145/3340531.3412174

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