DEA-C01 exam dumps

DEA-C01 practice question 12 of 550

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

DEA-C01 Question 12

Select 2

You are designing a data ingestion pipeline for a real-time analytics application that processes millions of events per second. The application requires low-latency ingestion and near-real-time processing. Which of the following AWS services are most suitable for this use case?

  1. A

    Amazon Kinesis Data Streams

  2. B

    Amazon S3

  3. C

    Amazon SQS

  4. D

    Amazon Managed Streaming for Apache Kafka (Amazon MSK)

  5. E

    AWS Glue

Show answer and explanation

Correct answers: A, D

Explanation

For real-time analytics applications requiring low-latency data ingestion, services like Amazon Kinesis Data Streams and Amazon MSK are ideal as they are specifically designed to handle high-throughput, real-time streaming workloads. Other services such as Amazon S3, Amazon SQS, and AWS Glue are not optimized for real-time streaming or low-latency requirements.

  • A. Correct.

    Amazon Kinesis Data Streams is designed for real-time data ingestion and processing with low latency, making it highly suitable for applications that require near-real-time analytics.

  • B. Incorrect.

    Amazon S3 is primarily a storage service optimized for durability and scalability rather than low-latency real-time ingestion. It is not suitable for real-time streaming analytics.

  • C. Incorrect.

    Amazon SQS is a message queuing service optimized for decoupling applications and processing messages asynchronously. It does not provide the low-latency real-time ingestion needed for this scenario.

  • D. Correct.

    Amazon Managed Streaming for Apache Kafka (Amazon MSK) supports low-latency streaming applications, making it well-suited for real-time data ingestion and processing.

  • E. Incorrect.

    AWS Glue is a serverless data integration service and is not designed for real-time ingestion or low-latency processing. It is better suited for ETL processes with batch processing.

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