DEA-C01 Question 111
Select 2You are designing a data pipeline to process and store clickstream data from a website in real-time. The data needs to be ingested, processed, and made queryable with minimal latency. Which combination of AWS services should you use to achieve this?
- A
Amazon Kinesis Data Streams for ingestion, AWS Lambda for processing, and Amazon DynamoDB for storage
- B
Amazon S3 for ingestion, AWS Glue for processing, and Amazon Athena for querying
- C
Amazon Kinesis Data Firehose for ingestion, AWS Lambda for processing, and Amazon Redshift for storage and querying
- D
Amazon Kinesis Data Streams for ingestion, AWS EMR for processing, and Amazon Elasticsearch (OpenSearch Service) for querying
- E
Amazon MQ for ingestion, AWS Lambda for processing, and Amazon S3 for storage
Show answer and explanation
Correct answers: A, C
Explanation
To design a real-time data pipeline, you need services optimized for low-latency ingestion, processing, and querying. Amazon Kinesis Data Streams or Kinesis Data Firehose are ideal for real-time ingestion. AWS Lambda provides serverless and low-latency processing, while Amazon DynamoDB and Amazon Redshift are optimized for storage and querying in real-time analytics scenarios.
- A. Correct.
This option is correct because Kinesis Data Streams can handle real-time data ingestion, Lambda can process the data with minimal latency, and DynamoDB provides a low-latency database for storage, making it suitable for real-time applications.
- B. Incorrect.
This option is incorrect because S3 is not designed for real-time ingestion or low-latency access. AWS Glue and Athena are more suitable for batch processing and querying rather than real-time processing.
- C. Correct.
This option is correct because Kinesis Data Firehose can handle real-time ingestion, Lambda can process the data, and Redshift is optimized for analytics and querying, making this a valid solution for real-time analytics.
- D. Incorrect.
This option is partially correct, but Amazon EMR is better suited for large-scale batch processing rather than low-latency real-time processing. Additionally, Elasticsearch (OpenSearch) may not meet low-latency requirements for querying in all scenarios.
- E. Incorrect.
This option is incorrect because Amazon MQ is not designed for high throughput real-time ingestion like Kinesis. Furthermore, S3 is not ideal for low-latency access or real-time data processing.