Migrate the data
Typically you will not need to make changes on the Configure CDC Capture page unless instructed to by StreamShift support. Click Configure CDC Apply to continue.
On the Configure CDC Apply page, you may be able to speed up data migration by creating table groups to allow StreamShift to migrate them in parallel. For example, if one table contains 50% of the data, moving it to its own table group could reduce migration time by up to half.
Typically you will not need to make other changes on this page unless instructed to by StreamShift support. Click Migrate Data to continue. Since data may be written out of order, to avoid errors StreamShift will not apply the foreign keys yet.
At the same time StreamShift starts initial load, it starts capturing insert, update, and delete operations in the source database using change data capture (CDC) and stores those events in the integrated Kafka instance. In the event this data consumes 60% of Kafka's available disk space, you will receive an email alert, and Striim operations staff will expand the virtual disks.
When initial load is complete, StreamShift starts applying the captured change data to the target database. This ongoing synchronization picks up where initial load stopped, and there should be no missing or duplicate transactions. Synchronization continues until you stop the migration manually.
When the migration of existing source data is complete, continuous synchronization from source to target using CDC starts automatically (see Lift and Shift versus Ongoing Synchronization).
At this point, for sources other than SQL Server, you may click Apply Constraints to restore the foreign keys.
If the source is SQL Server, Apply Constraints is disabled, and constraints will be applied when migration is stopped.