SAP-C02 Question 100
Single answerA company is migrating its on-premises data warehouse to AWS to handle large-scale analytical workloads. They want to minimize operational overhead, scale seamlessly based on demand, and store both structured and semi-structured data. Which AWS service is the most suitable for this use case?
- A
Amazon Redshift
- B
Amazon RDS
- C
Amazon DynamoDB
- D
Amazon S3 with Athena
Show answer and explanation
Correct answer: A
Explanation
Amazon Redshift is the best choice for large-scale analytical workloads because it is purpose-built for data warehousing and analytics. It supports structured and semi-structured data, scales seamlessly, and minimizes operational overhead. Other options like RDS, DynamoDB, and S3 with Athena serve different purposes and are not optimized for this use case.
- A. Correct.
Amazon Redshift is a fully managed data warehouse solution optimized for analytical workloads. It supports both structured and semi-structured data using features like native support for JSON and can scale seamlessly with features such as RA3 nodes and Redshift Spectrum.
- B. Incorrect.
Amazon RDS is a managed relational database primarily designed for transactional workloads rather than analytical workloads. It is not the ideal choice for large-scale analytics.
- C. Incorrect.
Amazon DynamoDB is a NoSQL database service designed for high-performance, low-latency key-value and document-based applications. It is not suitable for analytical workloads or data warehousing.
- D. Incorrect.
Amazon S3 with Athena allows querying data stored in S3 using SQL. While this combination is suitable for ad-hoc queries and data lake operations, it does not provide the same performance or optimized capabilities for large-scale analytical workloads as Amazon Redshift does.