Comparative Analysis of Database Query Storage Performance Between Stored Procedure and Function

Abednego Dwi Septiadi, Lee Jeong Bae


This research was conducted to measure the data storage time carried out by the DBMS on data that has been prepared with an increasing number of data, the data provided is consistent student data which will be stored with Stored Procedure and Function. This study uses the action research method which has 4 stages, starting with planning, action, observation and reflection. From the results of the experiments that have been carried out, it appears that Stored Procedure is able to outperform Function in data storage time. The data provided are 2 different types of data, each of which consists of 500, 2500, 4500 and 6500 data stages. This study also compares data storage that is differentiated by the computer between the data provider computer and the data storage computer or server, the result of which is the Stored Procedure. able to outperform Function in data storage speed.

Article Metrics

Abstract: 232 Viewers PDF: 103 Viewers


DMBS; Stored Procedure; Function; Query.

Full Text:



A. Rahadi, “ANALISIS DAN DESAIN SISTEM INFORMASI PERSEDIAAN BARANG BERBASIS KOMPUTER (Studi Kasus pada Toko Arta Boga),” J. Adm. Bisnis S1 Univ. Brawijaya, vol. 8, no. 2, p. 79908, 2014.

D. Frishman, K. Heumann, A. Lesk, and H. Mewes, “Intelligent Databases : Current Status,” vol. 14, no. 7, pp. 551–561, 1998.

S. Peck Lee and D. Zildzic, “Oracle Database Workload Performance Measurement and Tuning Toolkit,” Issues Informing Sci. Inf. Technol., vol. 3, pp. 371–381, 2006, doi: 10.28945/898.

D. C. P. Smith and N. Goodman, Data-Base Systems, vol. 11, no. 9. 1978.

A. Yusuf, “Strategi Genius Learning Dalam Pembelajaran Maharatul Kitabah,” Pendidik. Bhs. Arab, vol. 9, no. 20, p. 162, 2018.

B. W. M. Boog, “The Emancipatory Character of Action Research, its History and the Present State of the Art,” J. Community Appl. Soc. Psychol., vol. 13, no. 6, pp. 426–438, 2003, doi: 10.1002/casp.748.

Y. Li and S. Manoharan, “A performance comparison of SQL and NoSQL databases,” IEEE Pacific RIM Conf. Commun. Comput. Signal Process. - Proc., no. November, pp. 15–19, 2013, doi: 10.1109/PACRIM.2013.6625441.

S. Agrawal, V. Narasayya, and B. Yang, “Integrating vertical and horizontal partitioning into automated physical database design,” Proc. ACM SIGMOD Int. Conf. Manag. Data, pp. 359–370, 2004, doi: 10.1145/1007568.1007609.

T. Wahyuningsih, “Problems , Challenges and Opportunities Visualization on Big Data,” J. Appl. Data Sci., vol. 1, no. 1, pp. 20–28, 2020.

N. H. Trang, “Limitations of Big Data Partitions Technology,” J. Appl. Data Sci., vol. 1, no. 1, pp. 11–19, 2020.


  • There are currently no refbacks.

barcodeInternational Journal of Informatics and Information Systems (IJIIS)
ISSN: 2579-7069 (online)
Organized by Information System Department - Universitas Amikom Purwokerto - Indonesia, Laboratoire Signaux Et Systèmes (L2s) - Université Paris 13 - France, and Bright Publisher
Published by Bright Publisher
Website :
Email :,

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0