Cross-system data migration at petabyte scale: Best practices and frameworks

Enterprise context is different nowadays, and the process of regulating and migrating petabyte-scale data between heterogeneous systems is no longer an exception; it is a rather standard practice. Inspired by adopting cloud environments, modernization of the platforms, or legal changes, the demand for an effective, reliable, and sustainable cross-system data migration methodology has become a burning issue. The architectural underpinnings, implementations, performance stipulations, and transitive obstacles of the implementation of large-scale data migration across various environments and properties, including cloud data warehouses, legacy systems, and real-time platforms, are discussed in this review. The review uses the analysis of the current practice and case studies to analyze the state-of-the-art frameworks and find gaps in the current methodology. It ends by moving forward to explore automation, security, explainability, and sustainability within next-gen data migration ecosystems.

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Publication Details

Journal
World Journal of Advanced Engineering Technology and Sciences
Published
2025-07-30
DOI
https://doi.org/10.30574/wjaets.2025.16.1.1236
Primary Topic
Distributed and Parallel Computing Systems
Type
article
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article

Cross-system data migration at petabyte scale: Best practices and frameworks

Rajesh Sura
World Journal of Advanced Engineering Technology and Sciences
Distributed and Parallel Computing Systems
article

Cross-system data migration at petabyte scale: Best practices and frameworks

Rajesh Sura
article en

Abstract

Enterprise context is different nowadays, and the process of regulating and migrating petabyte-scale data between heterogeneous systems is no longer an exception; it is a rather standard practice. Inspired by adopting cloud environments, modernization of the platforms, or legal changes, the demand for an effective, reliable, and sustainable cross-system data migration methodology has become a burning issue. The architectural underpinnings, implementations, performance stipulations, and transitive obstacles of the implementation of large-scale data migration across various environments and properties, including cloud data warehouses, legacy systems, and real-time platforms, are discussed in this review. The review uses the analysis of the current practice and case studies to analyze the state-of-the-art frameworks and find gaps in the current methodology. It ends by moving forward to explore automation, security, explainability, and sustainability within next-gen data migration ecosystems.

World Journal of Advanced Engineering Technology and SciencesVol. 16(1)
Openalex Percentile: Top 79%
Distributed and Parallel Computing Systems
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