SAP-C02 Question 670
Single answerAn e-commerce company is building a real-time recommendation engine that analyzes customer browsing behavior and provides product suggestions instantly. The system must handle a high throughput of read and write requests with millisecond latency. Additionally, the recommendation data needs to be stored in a format that allows querying by specific attributes, such as category or user behavior patterns. Which AWS service or combination of services is the most appropriate for this use case?
- A
Amazon DynamoDB with DynamoDB Streams
- B
Amazon Aurora Serverless with MySQL
- C
Amazon ElastiCache for Redis
- D
Amazon RDS for PostgreSQL
Show answer and explanation
Correct answer: A
Explanation
The use case requires a database that can handle high-throughput, low-latency read and write operations while supporting attribute-based queries. Amazon DynamoDB is a fully managed NoSQL database that meets these criteria. Additionally, DynamoDB Streams can enable real-time data capture and processing, making it suitable for building a real-time recommendation engine. While ElastiCache is great for caching, it isn't designed for persistent storage or querying by attributes. Aurora Serverless and RDS are better suited for relational data models and do not match the requirements for millisecond latency and high throughput for NoSQL workloads.
- A. Correct.
Amazon DynamoDB with DynamoDB Streams is well-suited for high-throughput, low-latency use cases and supports querying by attributes. DynamoDB Streams can capture real-time item changes, making it ideal for a recommendation engine.
- B. Incorrect.
Amazon Aurora Serverless with MySQL is a good choice for relational database needs but is not optimized for millisecond latency or high throughput for NoSQL-style workloads.
- C. Incorrect.
Amazon ElastiCache for Redis provides low-latency caching but is not designed for primary data storage or querying by attributes, which is a requirement here.
- D. Incorrect.
Amazon RDS for PostgreSQL is a relational database service and is not suitable for handling high-throughput, low-latency NoSQL-style workloads or real-time data ingestion efficiently.