DEA-C01 exam dumps

DEA-C01 practice question 13 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 13

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You are designing a data ingestion pipeline for a real-time analytics application that processes millions of events per second. The system must minimize latency while maintaining high throughput. Which AWS services are best suited for this scenario?

  1. A

    Amazon Kinesis Data Streams

  2. B

    AWS Lambda

  3. C

    Amazon S3

  4. D

    Amazon Managed Streaming for Apache Kafka (Amazon MSK)

  5. E

    Amazon RDS

Show answer and explanation

Correct answers: A, D

Explanation

Amazon Kinesis Data Streams and Amazon MSK are optimized for real-time data ingestion with low latency and high throughput, both of which are essential for this scenario. While AWS Lambda, Amazon S3, and Amazon RDS are powerful services, they are not specifically designed for low-latency, high-throughput data ingestion. Lambda is for event-driven compute, S3 is for scalable storage, and RDS is for relational database use cases.

  • A. Correct.

    Amazon Kinesis Data Streams is designed for real-time ingestion with low latency and supports high throughput, making it a perfect fit for this use case.

  • B. Incorrect.

    AWS Lambda can process data but is not specifically a data ingestion service. It is better suited for event-driven compute rather than high-throughput ingestion.

  • C. Incorrect.

    Amazon S3 is highly durable and scalable for storage but is not designed for low-latency real-time ingestion. It's more suitable for batch processing or storing ingested data.

  • D. Correct.

    Amazon Managed Streaming for Apache Kafka (Amazon MSK) is a good choice for real-time data ingestion with low latency and high throughput, making it suitable for this scenario.

  • E. Incorrect.

    Amazon RDS is a relational database service and is not designed for real-time ingestion or high-throughput scenarios.

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