DEA-C01 Question 14
Select 2You are designing a data ingestion pipeline for a real-time analytics application that must process high volumes of streaming data with sub-second latency. Which AWS services are most appropriate for achieving the required throughput and latency characteristics?
- A
Amazon Kinesis Data Streams
- B
Amazon S3
- C
Amazon Managed Streaming for Apache Kafka (Amazon MSK)
- D
AWS Snowball
- E
Amazon SQS
Show answer and explanation
Correct answers: A, C
Explanation
For real-time analytics applications requiring high throughput and sub-second latency, Amazon Kinesis Data Streams and Amazon MSK are the most appropriate services. Both are designed to handle real-time streaming data ingestion with low latency. Other services, like Amazon S3 and AWS Snowball, are better suited for batch processing or bulk data transfer, while Amazon SQS is not optimized for real-time streaming.
- A. Correct.
Amazon Kinesis Data Streams is designed for real-time data ingestion and processing, offering high throughput and low latency. It is suitable for applications requiring sub-second processing of streaming data.
- B. Incorrect.
Amazon S3 is optimal for storing large volumes of data and batch processing but is not designed for real-time ingestion or low-latency streaming use cases.
- C. Correct.
Amazon Managed Streaming for Apache Kafka (Amazon MSK) is a fully managed service for real-time streaming data, supporting high throughput and low latency. It is a suitable choice for real-time analytics pipelines.
- D. Incorrect.
AWS Snowball is a physical device used for offline data transfer. It does not support real-time ingestion or low latency and is more suited for bulk data migration.
- E. Incorrect.
Amazon SQS is a message queuing service designed for decoupling applications. While it supports high throughput, it is not optimized for real-time streaming with sub-second latency requirements.