A company is moving its on-premises Oracle database to Amazon Aurora PostgreSQL. The database has several applications that write to the same tables. The applications need to be migrated one by one with a month in between each migration. Management has expressed concerns that the database has a high number of reads and writes. The data must be kept in sync across both databases throughout the migration. What should a solutions architect recommend?

The AWS Schema Conversion Tool (SCT) is essential for migrating an Oracle database to Aurora PostgreSQL, as it assesses and converts the schema and code. AWS Database Migration Service (DMS) is the appropriate tool for migrating the data, and a "full load plus change data capture (CDC)" task is necessary to perform an initial data load and then continuously replicate ongoing changes, keeping both databases in sync during the phased migration. A memory-optimized replication instance is recommended for high read/write workloads to ensure efficient processing of the data migration and CDC. Selecting all tables ensures complete data synchronization. Incorrect options: Using DataSync is incorrect because it is designed for file system or object storage migration, not relational databases. Using a compute-optimized instance might be insufficient for high read/write workloads, and selecting only the largest tables would not ensure complete data synchronization.