DEA-C01 Question 2
Single answerYou are working as a data engineer at a company that collects streaming data from IoT devices and ingests it into AWS for downstream analytics. The data needs to be ingested in near real-time and stored in a scalable and durable format for further processing. Which AWS service or combination of services would you choose to perform this data ingestion effectively?
- A
Amazon Kinesis Data Streams
- B
AWS Glue
- C
Amazon S3 Batch Operations
- D
Amazon Redshift
Show answer and explanation
Correct answer: A
Explanation
Amazon Kinesis Data Streams is the best choice for near real-time ingestion of streaming data, such as IoT device data, as it is designed to handle real-time data streams with high scalability and durability. Other services like AWS Glue, S3 Batch Operations, and Amazon Redshift serve different purposes and are not suitable for this use case.
- A. Correct.
Amazon Kinesis Data Streams is purpose-built for ingesting and processing real-time streaming data, making it the correct choice for near real-time data ingestion from IoT devices.
- B. Incorrect.
AWS Glue is primarily used for ETL (Extract, Transform, Load) operations and metadata management. While it is useful for data transformation, it is not ideal for real-time data ingestion.
- C. Incorrect.
Amazon S3 Batch Operations is designed for large-scale operations on existing S3 objects, such as copying or tagging, and is not suitable for real-time or near real-time data ingestion.
- D. Incorrect.
Amazon Redshift is a data warehouse service optimized for analytical queries but is not intended for real-time data ingestion.