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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:IJSREM67475

Automated Oracle Database Backup and Recovery Using RMAN

Stream/Area:

-

Subject:

-

Paper ID:

IJSREM67475

Volume:

10 |

9 |

Sep 2026

Pages:

1-5

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
Not assigned

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

ASM

Atharva Shashikant Mane

INFORMATION TECHNOLOGY AND COMPUTER SCIENCE

D.G. Ruparel College of Arts, Science And Commerce

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ASG

Aarti Sanjay Gawai

INFORMATION TECHNOLOGY AND COMPUTER SCIENCE

D.G. Ruparel College of Arts, Science And Commerce

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Abstract

Oracle Database is widely used for storing and managing critical data, making reliable backup and recovery essential for data protection and availability. Manual backup operations can require significant DBA effort and may result in missed backups or human errors. This research proposes an Automated Oracle Database Backup and Recovery system using Recovery Manager (RMAN). The proposed system uses RMAN scripts and Linux Cron scheduling to automate full backups, incremental backups, and archived redo log backups at predefined intervals. It also includes backup storage, monitoring, logging, backup validation, and recovery operations. The system is designed to reduce manual DBA intervention, improve backup consistency, minimise the risk of data loss, and support reliable database recovery. The proposed approach can be evaluated using parameters such as backup time, recovery time, storage usage, and backup success rate. The study also identifies challenges related to storage management, backup failures, scheduling errors, recovery complexity, and backup security. The proposed system provides a structured approach for automating Oracle database backup and recovery and can be further enhanced using cloud storage, intelligent monitoring, automated alerts, and advanced disaster recovery technologies.

KEYWORDS

Oracle Database RMAN Automated Backup Database Recovery Backup Scheduling Disaster Recovery.

Cite This Article

Atharva Shashikant Mane, Aarti Sanjay Gawai, "Automated Oracle Database Backup and Recovery Using RMAN," International Journal of Scientific Research in Engineering and Management, vol. 10, no. 9, pp. 1-5, Sep 2026.

Full Article/Conclusion

Automated database backup and recovery is an important requirement for maintaining data availability and reducing the risk of data loss. The reviewed studies show that automation can improve backup consistency, reduce manual work, support monitoring, and strengthen database security. They also highlight the importance of disaster recovery, backup validation, and reliable recovery processes. The literature also shows that existing research provides limited RMAN-specific experimental evaluation with reproducible testing and measurable backup and recovery parameters. Therefore, the proposed research focuses on Automated Oracle Database Backup and Recovery Using RMAN, with emphasis on automated scheduling, backup management, monitoring, and recovery. Overall, the proposed approach can provide a more consistent and reliable backup process while reducing manual DBA intervention. Future development can further extend the system through intelligent monitoring, cloud-based backup storage, stronger security mechanisms, and advanced disaster recovery techniques.

References

[1]  M. Ibrar et al., “Reconnoitering Data Protection and Recovery Strategies in the Cyber Environment: A Thematic Analysis,” International Journal for Electronic Crime Investigation, vol. 8, no. 4, 2024, doi: 10.54692/ijeci.2024.0804216. [2]   G. Ramesh, J. Logeshwaran, and V. Aravindarajan, “A Secured Database Monitoring Method to Improve Data Backup and Recovery Operations in Cloud Computing,” BOHR International Journal of Computer Science and Information Technology, vol. 2, no. 1, pp. 1–7, 2023, doi: 10.54646/bijcs.019. [3]    S. Sutar, K. Jose, V. Gaikwad, V. Mishra, D. Wankhede, and M. Karnik, “Enhancing Data Management: An Integrated Solution for Database Backup, Recovery, Conversion, and Encryption Capabilities,” International Journal of Intelligent Systems and Applications in Engineering, vol. 12, no. 6s, pp. 720–734, 2024. [4]     D. Yadav and S. Solanki, “Optimizing Oracle Database Security with Automated Backup and Recovery Solutions,” Journal of Quantum Science and Technology, vol. 1, no. 4, 2024, doi: 10.63345/jqst.v1i4.146. [5]   P. Manda, “Disaster Recovery by Design: Building Resilient Oracle Database Systems in Cloud and Hyperconverged Environments,” International Journal of Engineering and Technology Research, vol. 10, no. 2, pp. 16–27, 2025, doi: 10.34218/IJETR_10_02_002. [6]    H. Bhandari and R. C. Jaiswal, “Automation of Databases in Oracle,” International Journal for Research in Applied Science & Engineering Technology (IJRASET), vol. 11, no. XI, pp. 946–952, Nov. 2023, doi: 10.22214/ijraset.2023.56643. [7]  M. Dotasara and A. Sharma, “MDAS_DBRCC: Data Backup and Recovery Technique in Cloud Computing for Education Industry,” International Journal on Recent and Innovation Trends in Computing and Communication, vol. 10, no. 6, pp. 31–36, 2022, doi: 10.17762/ijritcc.v10i6.5621. [8]   P. Margol, P. Dymora, and M. Mazurek, “Database Backup and Recovery Strategies,” Advances in IT and Electrical Engineering, vol. 25, no. 36-3, 2017, doi: 10.7862/re.2017.15. [9]    P. Petrov, I. Kuyumdzhiev, G. Dimitrov, and A. Kremenska, “Relative Performance of Various Types of Repositories for MySQL Archive Backup and Restore Operations,” International Journal of Online and Biomedical Engineering, vol. 18, no. 13, 2022, doi: 10.3991/ijoe.v18i13.33429. [10]   H. Kim, H. Y. Yeom, and Y. Son, “An Efficient Database Backup and Recovery Scheme Using Write-Ahead Logging,” in 2020 IEEE 13th International Conference on Cloud Computing (CLOUD), Beijing, China,                     2020,          pp.       405–413,          doi: 10.1109/CLOUD49709.2020.00062.

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Publication Date

9/26/2026

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