SAA-C03 exam dumps

SAA-C03 practice question 369 of 553

AWS Certified Solutions Architect - Associate. Associate level, Amazon Web Services. Free question with the correct answer and a full explanation.

SAA-C03 Question 369

Single answer

A company needs to process a continuous stream of data in real-time from IoT sensors installed in their manufacturing units. The data needs to be ingested, processed in near real-time, and stored in Amazon S3 for long-term analysis. Which AWS service is the most appropriate for this use case?

  1. A

    Amazon Kinesis Data Streams

  2. B

    Amazon SQS

  3. C

    Amazon SNS

  4. D

    Amazon RDS

Show answer and explanation

Correct answer: A

Explanation

Amazon Kinesis Data Streams is the ideal choice for this scenario because it is purpose-built for ingesting and processing large streams of real-time data. It allows developers to build applications that require high-throughput and low-latency data processing, which is a perfect fit for the company's IoT sensor data use case. Once processed, the data can be sent to Amazon S3 for long-term storage and analysis.

  • A. Correct.

    Amazon Kinesis Data Streams is designed to collect and process large streams of data in real-time, making it the most suitable service for this use case. It can handle high-throughput data ingestion and integrates well with downstream processing and storage solutions like Amazon S3.

  • B. Incorrect.

    Amazon SQS is a fully managed message queuing service, but it is not designed for real-time streaming data processing. It is more suited for decoupling components of distributed systems using message queues.

  • C. Incorrect.

    Amazon SNS is a fully managed pub/sub messaging service that facilitates message delivery to multiple subscribers but is not designed for processing real-time data streams.

  • D. Incorrect.

    Amazon RDS is a relational database service and not suitable for ingesting or processing high-throughput real-time data streams. It is better suited for structured data storage and transactional workloads.

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