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Comparing data between two databases
The article presents an innovative approach to validating large-scale database migrations using chunk-based hashing instead of traditional row-by-row comparisons. The method significantly improved eff
iciency in comparing datasets between Oracle and Azure SQL Server while maintaining accuracy in a resource-constrained environment.

Reasons to Read -- Learn:

  • how to implement an efficient data validation strategy that can handle gigabytes of historical data using Python, with specific code examples and implementation details for comparing data between Oracle and SQL Server databases.
  • practical solution for validating sensitive data migrations in resource-constrained environments, using techniques that reduced processing time from traditional row-by-row comparisons to faster chunk-based hashing.
  • how to build a scalable data comparison system that generates detailed validation reports, including specific examples of handling different data types, managing database connections, and implementing error handling mechanisms.
    • 8 min readauthor: Mohammad Rohan
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