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Enhancing Oracle Database Migration with Cutting-Edge Techniques

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  • Krishna Anumula

Abstract

This article presents a comprehensive framework for large-scale Oracle database migrations, focusing on enterprise environments with complex requirements exceeding traditional migration approaches. Through examination of advanced techniques, including Oracle Golden Gate real-time replication, optimized RMAN backup strategies, and cascaded standby methodologies for databases exceeding 65TB, we establish practical patterns for successful implementations. The article addresses critical challenges, including SAN to ASM transitions, high availability preservation during migration, and robust data integrity validation techniques. We further explore automation frameworks that enhance migration reliability while reducing operational overhead, alongside security considerations essential for maintaining regulatory compliance throughout the transition process. Performance analysis demonstrates that properly executed migrations yield measurable improvements in both system performance and operational resilience, particularly when implementing structured disaster recovery testing methodologies. By integrating technical excellence with business continuity planning, organizations can achieve successful migrations while minimizing risk and disruption. The article findings provide database administrators and system architects with actionable strategies applicable across diverse industry sectors undertaking large-scale database modernization initiatives.

Suggested Citation

  • Krishna Anumula, 2025. "Enhancing Oracle Database Migration with Cutting-Edge Techniques," International Journal of Scientific Research in Computer Science, Engineering and Information Technology, International Journal of Scientific Research in Computer Science, Engineering and Information Technology, vol. 11(2), pages 1022-1034, March.
  • Handle: RePEc:jbh:ijsrcs:v11:y2025:i2:id:1169
    DOI: 10.32628/CSEIT25112424
    Note: Article URL: https://ijsrcseit.com/home/article/view/CSEIT25112424
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