SAP-C02 Question 551
Select 2A company is migrating its on-premises data analytics platform to AWS. The platform processes large amounts of data and requires high throughput for storage and compute. The company also wants a cost-efficient solution that supports parallel processing and can scale based on demand. Which combination of AWS services should the company use to achieve these requirements?
- A
Amazon S3 for storage and Amazon EMR for processing
- B
Amazon RDS with provisioned IOPS for storage and Amazon EC2 Auto Scaling for compute
- C
Amazon Redshift for storage and processing
- D
Amazon S3 for storage and AWS Glue for processing
- E
Amazon DynamoDB for storage and AWS Lambda for processing
Show answer and explanation
Correct answers: A, D
Explanation
The company requires a cost-efficient solution for large-scale data analytics that supports high throughput, parallel processing, and scalability. Amazon S3 and Amazon EMR form an ideal combination for this use case because S3 provides scalable, cost-effective storage, and EMR supports distributed processing frameworks like Apache Spark and Hadoop. Alternatively, Amazon S3 and AWS Glue can also be used for ETL and data processing pipelines, offering a scalable and serverless option.
- A. Correct.
Amazon S3 is a highly scalable and cost-efficient storage service that can handle large volumes of data. Amazon EMR is a managed service that allows you to process big data workloads using frameworks like Apache Spark and Hadoop, making this a suitable combination.
- B. Incorrect.
Amazon RDS with provisioned IOPS is designed for transactional databases and not optimized for analytics or parallel processing. While EC2 Auto Scaling can provide scalable compute, this option does not meet the requirements for high-throughput data analytics.
- C. Incorrect.
Amazon Redshift is a fully managed data warehouse service optimized for complex analytical queries on structured data. However, it is not suitable for unstructured data or use cases that require parallel processing frameworks like Apache Spark.
- D. Correct.
Amazon S3 provides scalable storage for large datasets at a low cost, while AWS Glue is a fully managed ETL service that can process data in parallel. This combination is well-suited for data analytics pipelines.
- E. Incorrect.
Amazon DynamoDB is a NoSQL database service optimized for key-value and document data, not for high-throughput analytics. AWS Lambda is serverless and suitable for event-driven compute but is not designed for large-scale data processing.