UDBMS: Road to Unification for Multi-model Data Management

Jiaheng Lu; Zhen Hua Liu; Pengfei Xu; Chao Zhang

doi:10.1007/978-3-030-01391-2_33

UDBMS: Road to Unification for Multi-model Data Management

Jiaheng Lu, Zhen Hua Liu, Pengfei Xu, Chao Zhang

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

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.

Original language	English
Title of host publication	Advances in Conceptual Modeling : ER 2018 Workshops Emp-ER, MoBiD, MREBA, QMMQ, SCME, Xi’an, China, October 22-25, 2018, Proceedings
Editors	Carson Woo, Jiaheng Lu, Zhanhuai Li, Tok Wang Ling, Guoliang Li, Mong Li Lee
Number of pages	10
Place of Publication	Cham
Publisher	Springer
Publication date	2019
Pages	285-294
ISBN (Print)	978-3-030-01390-5
ISBN (Electronic)	978-3-030-01391-2
DOIs	https://doi.org/10.1007/978-3-030-01391-2_33
Publication status	Published - 2019
MoE publication type	A4 Article in conference proceedings
Event	International Conference on Conceptual Modeling - Xi'an, China Duration: 22 Oct 2018 → 25 Oct 2018 Conference number: 37

Publication series

Name	Lecture Notes in Computer Science
Volume	11158
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Fields of Science

113 Computer and information sciences
DATABASE

Access to Document

10.1007/978-3-030-01391-2_33

UDBMS: Road to Unification for Multi-model Data ManagementFinal published version, 311 KB

Cite this

Lu, J., Liu, Z. H., Xu, P., & Zhang, C. (2019). UDBMS: Road to Unification for Multi-model Data Management. In C. Woo, J. Lu, Z. Li, T. W. Ling, G. Li, & M. L. Lee (Eds.), Advances in Conceptual Modeling : ER 2018 Workshops Emp-ER, MoBiD, MREBA, QMMQ, SCME, Xi’an, China, October 22-25, 2018, Proceedings (pp. 285-294). (Lecture Notes in Computer Science ; Vol. 11158). Springer. https://doi.org/10.1007/978-3-030-01391-2_33

Lu, Jiaheng ; Liu, Zhen Hua ; Xu, Pengfei et al. / UDBMS : Road to Unification for Multi-model Data Management. Advances in Conceptual Modeling : ER 2018 Workshops Emp-ER, MoBiD, MREBA, QMMQ, SCME, Xi’an, China, October 22-25, 2018, Proceedings. editor / Carson Woo ; Jiaheng Lu ; Zhanhuai Li ; Tok Wang Ling ; Guoliang Li ; Mong Li Lee. Cham : Springer, 2019. pp. 285-294 (Lecture Notes in Computer Science ).

@inproceedings{dc391d6a6b994658822bdc9192f635b4,

title = "UDBMS: Road to Unification for Multi-model Data Management",

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.",

keywords = "113 Computer and information sciences, DATABASE",

author = "Jiaheng Lu and Liu, {Zhen Hua} and Pengfei Xu and Chao Zhang",

year = "2019",

doi = "10.1007/978-3-030-01391-2_33",

language = "English",

isbn = "978-3-030-01390-5",

series = "Lecture Notes in Computer Science ",

publisher = "Springer",

pages = "285--294",

editor = "Carson Woo and Jiaheng Lu and Zhanhuai Li and Ling, {Tok Wang } and Guoliang Li and Lee, {Mong Li }",

booktitle = "Advances in Conceptual Modeling",

address = "United Kingdom",

note = "International Conference on Conceptual Modeling , ER 2018 ; Conference date: 22-10-2018 Through 25-10-2018",

}

Lu, J, Liu, ZH, Xu, P & Zhang, C 2019, UDBMS: Road to Unification for Multi-model Data Management. in C Woo, J Lu, Z Li, TW Ling, G Li & ML Lee (eds), Advances in Conceptual Modeling : ER 2018 Workshops Emp-ER, MoBiD, MREBA, QMMQ, SCME, Xi’an, China, October 22-25, 2018, Proceedings. Lecture Notes in Computer Science , vol. 11158, Springer, Cham, pp. 285-294, International Conference on Conceptual Modeling , Xi'an, China, 22/10/2018. https://doi.org/10.1007/978-3-030-01391-2_33

UDBMS: Road to Unification for Multi-model Data Management. / Lu, Jiaheng; Liu, Zhen Hua; Xu, Pengfei et al.
Advances in Conceptual Modeling : ER 2018 Workshops Emp-ER, MoBiD, MREBA, QMMQ, SCME, Xi’an, China, October 22-25, 2018, Proceedings. ed. / Carson Woo; Jiaheng Lu; Zhanhuai Li; Tok Wang Ling; Guoliang Li; Mong Li Lee. Cham: Springer, 2019. p. 285-294 (Lecture Notes in Computer Science ; Vol. 11158).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

TY - GEN

T1 - UDBMS

T2 - International Conference on Conceptual Modeling

AU - Lu, Jiaheng

AU - Liu, Zhen Hua

AU - Xu, Pengfei

AU - Zhang, Chao

N1 - Conference code: 37

PY - 2019

Y1 - 2019

N2 - 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.

AB - 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.

KW - 113 Computer and information sciences

KW - DATABASE

U2 - 10.1007/978-3-030-01391-2_33

DO - 10.1007/978-3-030-01391-2_33

M3 - Conference contribution

SN - 978-3-030-01390-5

T3 - Lecture Notes in Computer Science

SP - 285

EP - 294

BT - Advances in Conceptual Modeling

A2 - Woo, Carson

A2 - Lu, Jiaheng

A2 - Li, Zhanhuai

A2 - Ling, Tok Wang

A2 - Li, Guoliang

A2 - Lee, Mong Li

PB - Springer

CY - Cham

Y2 - 22 October 2018 through 25 October 2018

ER -

Lu J, Liu ZH, Xu P, Zhang C. UDBMS: Road to Unification for Multi-model Data Management. In Woo C, Lu J, Li Z, Ling TW, Li G, Lee ML, editors, Advances in Conceptual Modeling : ER 2018 Workshops Emp-ER, MoBiD, MREBA, QMMQ, SCME, Xi’an, China, October 22-25, 2018, Proceedings. Cham: Springer. 2019. p. 285-294. (Lecture Notes in Computer Science ). doi: 10.1007/978-3-030-01391-2_33