SAA-C03 Question 221
Select 2A company is designing a high-performing architecture for a real-time analytics application that ingests and processes millions of events per second from IoT devices. The application must ensure low-latency data processing and provide near real-time insights to users. Which combination of AWS services should the company use to achieve these requirements?
- A
Amazon Kinesis Data Streams for data ingestion and Amazon Kinesis Data Analytics for real-time processing
- B
Amazon SQS for data ingestion and AWS Lambda for processing
- C
Amazon DynamoDB for both data ingestion and real-time processing
- D
Amazon Kinesis Data Firehose for data ingestion and Amazon Redshift for real-time processing
- E
Amazon Kinesis Data Streams for data ingestion and AWS Lambda for processing
Show answer and explanation
Correct answers: A, E
Explanation
For a real-time analytics application that processes millions of events per second, Amazon Kinesis Data Streams is an ideal service for high-throughput, low-latency data ingestion. Amazon Kinesis Data Analytics can process this data in real-time, offering built-in analytics capabilities. Alternatively, AWS Lambda can be used alongside Kinesis Data Streams to process and transform streaming data in near real-time. Other services like SQS, DynamoDB, Firehose, and Redshift are not designed to handle this specific real-time, high-throughput use case effectively.
- A. Correct.
Correct: Amazon Kinesis Data Streams is designed for high-throughput real-time data ingestion, and Amazon Kinesis Data Analytics provides built-in capabilities for real-time data processing and analytics.
- B. Incorrect.
Incorrect: While Amazon SQS can handle message ingestion, it is not optimized for real-time streaming of millions of events per second. AWS Lambda is event-driven but better suited for smaller-scale processing tasks.
- C. Incorrect.
Incorrect: Amazon DynamoDB is a NoSQL database and is not designed for real-time ingestion or stream processing at scale. It is better for storing and querying data.
- D. Incorrect.
Incorrect: While Amazon Kinesis Data Firehose is useful for data delivery, it is not designed for real-time streaming. Amazon Redshift is optimized for data warehousing and batch analytics, not real-time processing.
- E. Correct.
Correct: Amazon Kinesis Data Streams is excellent for real-time ingestion of high-throughput data, and AWS Lambda can process these events in near real-time as they arrive.