A company currently has data hosted in an IBM Db2 database. A web application calls an API that runs stored procedures on the database to retrieve user information data that is read-only. This data is historical in nature and changes on a daily basis. When a user logs in to the application, this data needs to be retrieved within 3 seconds. Each time a user logs in, the stored procedures run. Users log in several times a day to check stock prices.
Running this database has become cost-prohibitive due to Db2 CPU licensing. Performance goals are not being met. Timeouts from Db2 are common due to long-running queries.
Which approach should a solutions architect take to migrate this solution to AWS?

A. Rehost the Db2 database in Amazon Fargate. Migrate all the data. Enable caching in Fargate. Refactor the API to use the Fargate Db2 database. Implement Amazon API Gateway and enable API caching.
B. Use AWS DMS to migrate data to Amazon DynamoDB using a continuous replication task. Refactor the API to use the DynamoDB data. Implement the refactored API in Amazon API Gateway and enable API caching.
C. Create a local cache on the mainframe to store query outputs. Use SFTP to sync to Amazon S3 on a daily basis. Refactor the API to use Amazon EFS. Implement Amazon API Gateway and enable API caching.
D. Extract data daily and copy the data to AWS Snowball for storage on Amazon S3. Sync daily. Refactor the API to use the S3 data. Implement Amazon API Gateway and enable API caching.