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ISSN: 2582-8266 (Online)  || UGC Compliant Journal || Google Indexed || Impact Factor: 9.48 || Crossref DOI

Fast Publication within 2 days || Low Article Processing charges || Peer reviewed and Referred Journal

Research and review articles are invited for publication in Volume 18, Issue 3 (March 2026).... Submit articles

Digital twin technology for predictive database migration: The future of risk-free data transitions

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  • Digital twin technology for predictive database migration: The future of risk-free data transitions

Ellavarasan Asokan *

Anna University, India.

Review Article

World Journal of Advanced Engineering Technology and Sciences, 2025, 15(01), 645-659

Article DOI: 10.30574/wjaets.2025.15.1.0269

DOI url: https://doi.org/10.30574/wjaets.2025.15.1.0269

Received on 28 February 2025; revised on 07 April 2025; accepted on 09 April 2025

Digital twin technology offers a transformative solution for one of enterprise IT's most challenging operations: database migrations. By creating virtual replicas of database environments, organizations can simulate migration processes before implementation, significantly reducing risks associated with downtime, data integrity issues, and performance degradation. The integration of artificial intelligence with digital twins enables accurate prediction of migration outcomes, automated detection of potential bottlenecks, and optimization of migration strategies. While implementing digital twins for database migrations presents challenges in synchronization, computational resources, and simulation accuracy, the technology provides unprecedented visibility into migration complexities. As digital twins mature, they promise to evolve database migrations from high-risk events into continuous, seamless processes with minimal business impact, fundamentally changing how organizations approach database modernization and technology transitions. 

Database Migration; Digital Twins; Predictive Simulation; Self-Healing Technology; Continuous Evolution

https://wjaets.com/sites/default/files/fulltext_pdf/WJAETS-2025-0269.pdf

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Ellavarasan Asokan. Digital twin technology for predictive database migration: The future of risk-free data transitions. World Journal of Advanced Engineering Technology and Sciences, 2025, 15(01), 645-659. Article DOI: https://doi.org/10.30574/wjaets.2025.15.1.0269.

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