SAP-C02 Question 321
Select 2A company is developing a new application for managing e-commerce transactions. The application requires low-latency access to product catalogs, the ability to process millions of transactions per second, and support for complex queries, such as searching for products by multiple attributes. Additionally, the application must analyze customer purchasing patterns to provide personalized recommendations. Which combination of AWS purpose-built databases should the company use to meet these requirements?
- A
Amazon DynamoDB for product catalogs and Amazon Redshift for customer purchasing analysis
- B
Amazon RDS for product catalogs and Amazon Neptune for customer purchasing analysis
- C
Amazon DynamoDB for product catalogs and Amazon Neptune for customer purchasing analysis
- D
Amazon ElastiCache for product catalogs and Amazon Redshift for customer purchasing analysis
- E
Amazon Timestream for product catalogs and Amazon Aurora for customer purchasing analysis
Show answer and explanation
Correct answers: A, C
Explanation
To meet the requirements of this e-commerce application, the company needs to leverage purpose-built databases optimized for their specific workloads. Amazon DynamoDB is ideal for low-latency, high-throughput transactions, such as managing product catalogs. For customer purchasing analysis, Amazon Redshift can handle complex queries and large-scale analytics, while Amazon Neptune can analyze relationships, such as connections between products and customers. Combining these services satisfies both the transactional and analytical requirements of the application.
- A. Correct.
Amazon DynamoDB is a highly scalable, low-latency NoSQL database suitable for product catalogs requiring high throughput. Amazon Redshift is a data warehouse optimized for analytical queries, making it ideal for analyzing customer purchasing patterns.
- B. Incorrect.
Amazon RDS is a relational database service that supports complex queries, but it is not optimized for low-latency, high-throughput workloads like product catalogs. Amazon Neptune is a graph database designed for relationship-based queries, not for customer purchasing analysis.
- C. Correct.
Amazon DynamoDB is the right choice for low-latency, high-throughput product catalogs. Amazon Neptune can be used to analyze relationships and connections, such as customer purchasing patterns in a graph structure.
- D. Incorrect.
Amazon ElastiCache is an in-memory data store ideal for caching, not for primary product catalogs. Amazon Redshift is suitable for customer purchasing analysis but is not paired well with ElastiCache for this use case.
- E. Incorrect.
Amazon Timestream is designed for time-series data, not product catalogs. Amazon Aurora is a relational database service, but it is not purpose-built for analyzing purchasing patterns at scale.