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Cited by 63Advanced Database Systems and QueriesCloud Computing and Resource ManagementDistributed systems and fault tolerance

The DOI matches its Crossref record.

SQL, NewSQL, and NOSQL Databases: A Comparative Survey

Khasawneh, Tariq N., AL-Sahlee, Mahmoud H., Safia, Ali A.·2020·2020 11th International Conference on Information and Communication Systems (ICICS)
DOI 10.1109/icics49469.2020.239513
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Abstract

Non-relational databases have proved to be a viable alternative to the traditional relational database management systems, especially with the ever-increasing volume of data. Also known as "NoSQL" database systems, a scalable management system enabling handling such volumes of data. This work aims at providing an overview of the different NoSQL management systems, classifying them into four main categories: key-value stores, column-oriented, document-oriented, and graph oriented, comparing each of the categories using multiple criteria including the CAP theorem and BASE properties.

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Crossref · 10.1109/icics49469.2020.239513

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Citations

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Research works printed but not linked: 17

  1. kumar, 2014, Apache Hadoop, NoSQL and NewSQL solutions of big data, International Journal of Advance Foundation and Research in Science & Engineering (IJAFRSE), 1, 28
  2. acharya, 0, SURVEY ON NoSQL DATABASE CLASSIFFICATION NEW ERA OF DATABASES FOR BIG DATA
  3. han, 2011, Survey on NoSQL database, 2011 6th International Conference on Pervasive Computing and Applications, 363
  4. 10.1186/s40537-015-0025-0 · DOI
  5. 10.1016/j.is.2016.07.009 · DOI
  6. 10.1145/1323293.1294281 · DOI
  7. khetrapal, 2006, HBase and Hypertable for Large Scale Distributed Storage Systems
  8. 0, Database Differences Microsoft SQL Server vs Oracle Database
  9. kumar, 2014, Critical analysis of database management using newsql, International Journal of Computer Science and Mobile Computing, 3, 434
  10. 10.1145/1721654.1721659 · DOI
  11. stonebraker, 2013, The VoltDB Main Memory DBMS, IEEE Data Eng Bull, 36, 21
  12. 10.14257/ijdta.2014.7.6.11 · DOI
  13. stonebraker, 1986, The Design of POSTGRES, 15, 340
  14. 0, Graph Database
  15. 10.1109/PACRIM.2013.6625441 · DOI
  16. 10.1186/s40537-015-0025-0 · DOI
  17. 2017, A Survey of Non -Relational Databases with Big Data, International Journal on Recent and Innovation Trends in Computing and Communication, 5, 143

Cited by

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Metadata

Authors
Khasawneh, T. N., AL-Sahlee, M. H., & Safia, A. A.
Affiliations
Princess Sumaya University for Technology (JO)
Venue
2020 11th International Conference on Information and Communication Systems (ICICS)
Publisher
IEEE
Published
2020-04
Pages
013-021
DOI
10.1109/icics49469.2020.239513
OpenAlex
W3021358426
Cited by
63
References
0
Citations by year
2026: 5 · 2025: 7 · 2024: 8 · 2023: 12 · 2022: 10 · 2021: 16 · 2020: 5
FWCI
9.02
Type
conference paper
Language
en
Open access
closed
Licence
Locations
International Conference on Information and Communication Systems (ICICS) (publishedVersion)
Topics
  • Physical Sciences › Computer Science › Information Systems › Advanced Database Systems and Queries
  • Physical Sciences › Computer Science › Information Systems › Cloud Computing and Resource Management
  • Physical Sciences › Computer Science › Computer Networks and Communications › Distributed systems and fault tolerance
Keywords
NoSQL databases, NewSQL, SQL database, relational database management systems, key-value stores, column-oriented databases, document-oriented databases, graph databases, CAP theorem, scalability, data volume

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CoChat. (2026). Citation check: SQL, NewSQL, and NOSQL Databases: A Comparative Survey. https://app.cochat.ai/papers/10.1109/icics49469.2020.239513
The paper
Khasawneh, T. N., AL-Sahlee, M. H., & Safia, A. A. (2020). SQL, NewSQL, and NOSQL Databases: A Comparative Survey. 2020 11th International Conference on Information and Communication Systems (ICICS). https://doi.org/10.1109/icics49469.2020.239513

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.