Lesson Learned #463: Synchronizing Large Data Volumes Between SQL Databases: A Python Solution
While working on a support case, we faced the need to replicate a substantial volume of data in a table to conduct performance comparisons between two different SQL databases. During this troubleshooting process, we crafted a small yet powerful Python script to accomplish this task, which might be beneficial in similar scenarios. Given that the source table contained several million records, the utilization of multithreading was crucial to handle this massive data efficiently. Moreover, every execution of the script clearly indicated the GUID of the most recently processed data, adding a layer of traceability to our operations. As always, this script serves as an example and should be thoroughly tested in a controlled environment, with users taking responsibility for its deployment.
