DEA-C01 Question 176
Select 2A company is planning to migrate its on-premises data warehouse to AWS. Their existing data is structured and stored in a relational database, while some of their new data is semi-structured and arriving in real-time. They want to enable analytics on both historical and real-time data post-migration. Which combination of AWS services best aligns with their data storage and migration requirements?
- A
Amazon Redshift for historical structured data and Amazon Kinesis Data Streams for real-time data ingestion
- B
Amazon S3 for all data storage and AWS Glue for real-time data transformation
- C
Amazon DynamoDB for storing both historical and real-time data
- D
Amazon Redshift Spectrum for querying historical data in S3 and Amazon Kinesis Data Firehose for real-time data delivery
- E
Amazon Aurora for storing historical structured data and Amazon SQS for real-time data processing
Show answer and explanation
Correct answers: A, D
Explanation
To align data storage and migration requirements, the combination of Amazon Redshift and Amazon Kinesis Data Streams (or Kinesis Data Firehose) enables efficient analytics on historical structured data and real-time data ingestion/delivery. Redshift provides a scalable data warehouse for structured data, while Kinesis services handle real-time data ingestion, ensuring the architecture meets both historical and real-time analytics needs.
- A. Correct.
Correct: Amazon Redshift is optimized for structured data analytics, and Amazon Kinesis Data Streams is suitable for ingesting real-time data streams, aligning with the requirements for both historical and real-time data.
- B. Incorrect.
Incorrect: Amazon S3 is a general-purpose object storage service but lacks optimization for structured analytics. AWS Glue is primarily a data transformation tool, not a real-time ingestion solution.
- C. Incorrect.
Incorrect: Amazon DynamoDB is a NoSQL database optimized for key-value and document-based workloads, not suitable for analytics on structured or real-time data.
- D. Correct.
Correct: Amazon Redshift Spectrum allows querying historical data directly in S3 without moving it into Redshift, and Amazon Kinesis Data Firehose is ideal for real-time data delivery to analytics services.
- E. Incorrect.
Incorrect: Amazon Aurora is a relational database service but is not optimized for analytical workloads. Amazon SQS is a message queuing service, not designed for real-time data processing and analytics.