A company is migrating an on-premises application to AWS and plans to use Amazon Redshift. Which of the following use cases are suitable for Amazon Redshift in this scenario? (Choose three.)
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Correct answer: Supporting client-side and server-side encryption, Building analytics workloads during specified hours and when the application is not active, Scaling globally to support petabytes of data and tens of millions of requests per minute.
Why this is the answer
Amazon Redshift is a fully managed, petabyte-scale data warehouse service designed for analytical workloads. It supports both client-side and server-side encryption for data security. Redshift is ideal for building analytics workloads, especially for batch processing during off-peak hours, as it can efficiently process large datasets. While Redshift can scale to petabytes of data, its primary strength is analytical queries, not high-volume transactional requests (tens of millions per minute) typically handled by services like Amazon DynamoDB or Aurora. Redshift is not designed for caching data to reduce pressure on an operational database; that's a use case for services like ElastiCache. It also doesn't natively support creating secondary replicas for high availability in the same way a transactional database might; it uses snapshots for recovery. Data APIs are better served by transactional databases or specialized API gateways.
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