SAA-C03 Question 349
Single answerA company needs to ingest data from IoT devices deployed across multiple regions. The data is generated continuously and needs to be processed in real-time for analytics and anomaly detection. Which solution provides the most efficient and scalable data ingestion pattern for this use case?
- A
Use Amazon Kinesis Data Streams to ingest the data from IoT devices and process it in real-time.
- B
Use Amazon S3 to store the data from IoT devices and run batch processing jobs periodically.
- C
Use Amazon Simple Queue Service (SQS) to collect messages from IoT devices and trigger AWS Lambda for real-time processing.
- D
Use AWS DataSync to transfer data from IoT devices to an on-premises data pipeline for real-time processing.
Show answer and explanation
Correct answer: A
Explanation
Amazon Kinesis Data Streams is specifically designed for real-time data ingestion and processing, making it the most suitable choice for scenarios involving continuous data generation, such as IoT devices. It allows for scalable, low-latency data streaming and can integrate with other AWS services for real-time analytics and anomaly detection. Other options, like S3 and SQS, do not meet the requirement for real-time data ingestion and processing, while AWS DataSync is focused on data migration rather than streaming.
- A. Correct.
This is the correct answer. Amazon Kinesis Data Streams is designed for real-time data streaming and can efficiently handle continuous data ingestion from IoT devices while enabling real-time processing.
- B. Incorrect.
This is incorrect. While Amazon S3 is a scalable storage solution, it is not optimized for real-time data ingestion and processing. It is better suited for batch processing and archival use cases.
- C. Incorrect.
This is incorrect. Amazon SQS is a message queueing service that can be used for decoupling applications but is not ideal for high-throughput, real-time data streaming scenarios.
- D. Incorrect.
This is incorrect. AWS DataSync is primarily used for data migration and replication between on-premises environments and AWS. It is not suitable for real-time data ingestion and processing from IoT devices.