Multi-SQL: An extensible multi-model data query language

TL;DR

Multi-SQL is a novel, extensible query language designed for unified management of diverse data models in multi-model data hubs, enabling flexible, efficient querying across various data types.

Contribution

It introduces the first multi-model query language, Multi-SQL, with formal semantics and a two-level implementation approach to enhance query efficiency.

Findings

Multi-SQL supports various data models with formal semantics.

The two-level implementation improves query execution efficiency.

Multi-SQL is extensible to accommodate additional data models.

Abstract

Big data management aims to establish data hubs that support data in multiple models and types in an all-around way. Thus, the multi-model database system is a promising architecture for building such a multi-model data store. For an integrated data hub, a unified and flexible query language is incredibly necessary. In this paper, an extensible and practical query language--Multi-SQL is proposed to realize the unified management of multi-model data considering the co-processing of multi-model data. To the best of our knowledge, Multi-SQL is the first query language based on various data models. Multi-SQL can also be expanded to suit more complicated scenarios as it is flexible to support other data models. Moreover, we provide a formal semantic definition of the core features of Multi-SQL, including the multi-model definition, multi-model filters, multi-model joins, etc. Furthermore, we propose a two-level query implementation method to totally exploit the existing query optimization capabilities of the underlying engines which could largely improve the query excution efficiency.