SAP-C02 Question 671
Select 2A company is designing a data platform to support an e-commerce application. The platform needs to handle high transaction volumes for order processing, provide low-latency caching for frequently accessed data like product details, and support analytics workloads for reporting and business intelligence. Which combination of purpose-built AWS databases and services should the company use?
- A
Amazon DynamoDB for order processing, Amazon ElastiCache for caching, and Amazon Redshift for analytics workloads
- B
Amazon Aurora Serverless for order processing, Amazon ElastiCache for caching, and Amazon Redshift for analytics workloads
- C
Amazon RDS for PostgreSQL for order processing, Amazon DynamoDB Accelerator (DAX) for caching, and Amazon Redshift for analytics workloads
- D
Amazon DynamoDB for order processing, Amazon ElastiCache for caching, and Amazon RDS for MySQL for analytics workloads
- E
Amazon Aurora Serverless for order processing, Amazon ElastiCache for caching, and Amazon Athena for analytics workloads
Show answer and explanation
Correct answers: A, B
Explanation
Purpose-built databases are optimized for specific use cases. DynamoDB and Aurora Serverless are well-suited for high-volume or variable workload order processing. ElastiCache is an in-memory data store that provides low-latency caching. For analytics workloads, Amazon Redshift is a data warehouse purpose-built to handle large-scale analytics queries. Combining these services ensures optimal performance for each part of the application.
- A. Correct.
Correct: Amazon DynamoDB is ideal for high-volume order processing due to its scalability and low-latency performance. ElastiCache provides in-memory caching for frequently accessed data, and Redshift is purpose-built for analytics workloads.
- B. Correct.
Correct: Amazon Aurora Serverless is suitable for order processing with variable workloads as it automatically scales. ElastiCache offers low-latency caching, and Redshift is optimized for analytics workloads.
- C. Incorrect.
Incorrect: Amazon RDS for PostgreSQL is not as well-suited for high-transaction workloads or low-latency requirements compared to DynamoDB or Aurora Serverless. Additionally, DAX is a caching layer specifically for DynamoDB, not a general-purpose cache.
- D. Incorrect.
Incorrect: While DynamoDB and ElastiCache are suitable for order processing and caching, Amazon RDS for MySQL is not optimized for analytics workloads compared to Redshift.
- E. Incorrect.
Incorrect: Aurora Serverless and ElastiCache are valid choices for order processing and caching, but Amazon Athena is not a database; it is a query service for analyzing data stored in Amazon S3, which is not the described use case.