DEA-C01 Question 179
Single answerA company is migrating its on-premises data warehouse to AWS and needs to ensure the data storage solution aligns with their requirements for scalability, low-latency access, and compatibility with their existing analytics tools. The migration involves structured data and requires regular batch updates. Which solution best aligns with these requirements?
- A
Migrate the data to Amazon S3 and query it using Amazon Athena.
- B
Migrate the data to Amazon Redshift and use AWS Glue for batch updates.
- C
Store the data in Amazon DynamoDB for low-latency access and scalability.
- D
Use Amazon RDS with a PostgreSQL database for structured data and batch updates.
Show answer and explanation
Correct answer: B
Explanation
The scenario describes a need for a scalable data warehouse that provides low-latency access and supports structured data with batch updates. Amazon Redshift is purpose-built for such use cases, offering integration with analytics tools, scalability, and high performance. When paired with AWS Glue, it can efficiently handle batch updates, making it the best fit for the given requirements.
- A. Incorrect.
While Amazon S3 and Amazon Athena offer scalable and serverless querying, they are not optimized for low-latency, structured data analytics compared to Amazon Redshift. This option is better suited for ad-hoc querying and unstructured data.
- B. Correct.
Amazon Redshift is a fully managed data warehouse designed for scalable and low-latency access to structured data. It is compatible with analytics tools and supports batch updates when integrated with AWS Glue, making it an ideal solution for the scenario.
- C. Incorrect.
Amazon DynamoDB is a NoSQL database optimized for key-value and document-based workloads. It is not suitable for structured data warehousing or analytics, making it a poor choice for this scenario.
- D. Incorrect.
Amazon RDS with PostgreSQL is a relational database service that supports structured data and batch updates. However, it is not designed for large-scale data warehousing or analytics, and it lacks the scalability and performance of Amazon Redshift for such use cases.