CFP last date
20 January 2025
Call for Paper
February Edition
IJCA solicits high quality original research papers for the upcoming February edition of the journal. The last date of research paper submission is 20 January 2025

Submit your paper
Know more
The week's pick
Responsive image
SFLA-Based Line Balancing and Task Optimization in Master-Slave Controlled Hanger Transportation Systems for Garment Production

Duc Hoang Nguyen
Random Articles
Reseach Article

Comparison of Techniques for Storing JSON Data in Relational Form

by Dušan Petković
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 185 - Number 22
Year of Publication: 2023
Authors: Dušan Petković
10.5120/ijca2023922962

Dušan Petković . Comparison of Techniques for Storing JSON Data in Relational Form. International Journal of Computer Applications. 185, 22 ( Jul 2023), 9-12. DOI=10.5120/ijca2023922962

@article{ 10.5120/ijca2023922962,
author = { Dušan Petković },
title = { Comparison of Techniques for Storing JSON Data in Relational Form },
journal = { International Journal of Computer Applications },
issue_date = { Jul 2023 },
volume = { 185 },
number = { 22 },
month = { Jul },
year = { 2023 },
issn = { 0975-8887 },
pages = { 9-12 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume185/number22/32822-2023922962/ },
doi = { 10.5120/ijca2023922962 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T01:26:44.068259+05:30
%A Dušan Petković
%T Comparison of Techniques for Storing JSON Data in Relational Form
%J International Journal of Computer Applications
%@ 0975-8887
%V 185
%N 22
%P 9-12
%D 2023
%I Foundation of Computer Science (FCS), NY, USA
Abstract

JSON (JavaScript Object Notation) has become popular as the data exchange format over the Web. Recently, JSON has been gaining more popularity over XML due to its simplicity and ability to fit into the programming languages’ data types. At the beginning, JSON data have been stored by document store systems. Since the publication of the SQL/JSON specification in the SQL standard, several relational database vendors have integrated the support of JSON in their database systems. In this paper we compare two forms of storing JSON data into relational tables in respect to data load time and disk space usage. Our experimental results show that the native (binary) storage form occupies approximately 56% of disk space needed for the row storage form. Also, the former outperforms the latter in relation to data loading time.

References
  1. ISO/IEC TR 9075-6:2017 Information technology, DB languages: SQL Technical Reports Support for JavaScript Object Notation, http://standards.iso.org/ ittf/PubliclyAvailableStandards/index.html .
  2. Petković, D. SQL/JSON Standard: Properties and Deficiencies. Datenbank Spektrum 17, 277–287 (2017). https://doi.org/10.1007/s13222-017-0267-4 .
  3. Piech,M., Marcjan,R., A New Approach to Storing Dynamic Data in Relational Databases Using JSON, Computer Science, 19(1) (2018), https://doi.org/10.7494/csci.2018.19.1.2505 .
  4. Bahta,R., Atay,M., Translating JSON data into relational data using schema-oblivious approaches, ACM Southeast Conference, Kennesaw, USA, 2019, https://doi.org/10.1145/3299815.3314467.
  5. Petković, D. Non-native Techniques for Storing JSON Documents into Relational Tables, Proc. of the 22nd Int. Conf. on Information Integration and Web-based Appl. & Services, 2020, https://doi.org/10.1145/3428757.3429103.
  6. Liu, Z.H., Hammerschmidt, B., McMahon, D., Chang, H., Native JSON Datatype Support: Maturing SQL and NoSQL Convergence in Oracle Database, Proc. Of the VLDB Endovment, Vol. 13(12), 2020, https://doi.org/10.14778/3415478.3415534.
  7. Atay,M., Chebotko, A., Liu, D., Lu, S., Fotouhi, F., Efficient Schema-based XML-to-Relational data mapping. Information Systems Journal 32 (3), 2007, https://doi.org/10.1016/j.is.2005.12.008.
  8. Shanmugasundaram, J. et al., Relational Databases for Querying XML Documents: Limitations and Opportunities, VLDB, 1999, pp. 302–314, Edinburgh.
  9. Lee, D. Chu, W., Constraints-preserving Transformation from XML Document Type Definition to Relational Schema, ER, Salt Lake City, USA 2000.
  10. Florescu, D., Kossmann,D., Storing and Querying XML Data Using an RDBMS, IEEE Data Eng. Bull. 22 (3) (1999), pp. 27–34.
  11. Yoshikawa, M., Amagasa, T., Shimura, T., Uemura, S., XRel: A Path-Based Approach to Storage and Retrieval of XML Documents using Relational Databases. ACM Trans. on Internet Technology, 2001, https://doi.org/10.1145/383034.383038.
  12. Petković, D., Storing XML documents in databases using existing object-relational features, - Proc. of the Fifth Balkan Conference in Informatics, 2012, https://doi.org/10.1145/2371316.2371373 .
  13. Zip Code Data Sample, https://catalog.data.gov/dataset/cadastral-plss-standardized-data-plssspecialsurvey-se-version-1,last accessed2023/05/01
Index Terms

Computer Science
Information Sciences

Keywords

RDBMSs JSON native storage row document storage

Powered by PhDFocusTM