What is a common technique to minimize downtime during critical database migration?

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Multiple Choice

What is a common technique to minimize downtime during critical database migration?

Explanation:
Minimizing downtime during a critical database migration relies on keeping the target in near real-time sync with the source while you prepare for a quick cutover. Change Data Capture continuously captures changes from the source and applies them to the target, so after the initial full load most of the work is already done and the target reflects the current state. When you perform the final switch, it happens within a scheduled maintenance window, allowing you to redirect traffic and complete validation with only a brief interruption. Having a rollback plan adds safety: if validation reveals issues, you can revert to the source quickly and avoid extended downtime or data inconsistency. This approach contrasts with a full dump-and-reload, which would cause a longer outage; delaying validation after cutover risks moving forward with problems; or using a single data-only move, which ignores ongoing changes and can lead to data drift.

Minimizing downtime during a critical database migration relies on keeping the target in near real-time sync with the source while you prepare for a quick cutover. Change Data Capture continuously captures changes from the source and applies them to the target, so after the initial full load most of the work is already done and the target reflects the current state. When you perform the final switch, it happens within a scheduled maintenance window, allowing you to redirect traffic and complete validation with only a brief interruption. Having a rollback plan adds safety: if validation reveals issues, you can revert to the source quickly and avoid extended downtime or data inconsistency. This approach contrasts with a full dump-and-reload, which would cause a longer outage; delaying validation after cutover risks moving forward with problems; or using a single data-only move, which ignores ongoing changes and can lead to data drift.

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