Multi-model Databases | Zendy

Jiaheng Lu | Zendy; Irena Holubová | Zendy

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Multi-model Databases

Author(s) -

Jiaheng Lu,

Irena Holubová

Publication year - 2019

Publication title -

acm computing surveys

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 2.079

H-Index - 163

eISSN - 1557-7341

pISSN - 0360-0300

DOI - 10.1145/3323214

Subject(s) - computer science , database , database design , data model (gis) , database model , data modeling , variety (cybernetics) , perspective (graphical) , physical data model , database theory , data administration , data science , database testing , data mining , database schema , artificial intelligence

The variety of data is one of the most challenging issues for the research and practice in data management systems. The data are naturally organized in different formats and models, including structured data, semi-structured data, and unstructured data. In this survey, we introduce the area of multi-model DBMSs that build a single database platform to manage multi-model data. Even though multi-model databases are a newly emerging area, in recent years, we have witnessed many database systems to embrace this category. We provide a general classification and multi-dimensional comparisons for the most popular multi-model databases. This comprehensive introduction on existing approaches and open problems, from the technique and application perspective, make this survey useful for motivating new multi-model database approaches, as well as serving as a technical reference for developing multi-model database applications.

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