DEA-C01 Question 161
Select 2You are designing a data lake architecture for a large e-commerce company. The system must handle a mix of structured, semi-structured, and unstructured data. Additionally, the solution should support low-latency queries for recent transactional data, while archival data can be accessed less frequently. Which combination of AWS storage platforms is most suitable for this use case?
- A
Amazon S3 for the data lake and Amazon Redshift for low-latency analytics
- B
Amazon RDS for storing all data types and running analytics
- C
Amazon DynamoDB for unstructured data and Amazon S3 for structured data
- D
Amazon S3 for the data lake and Amazon Athena for querying archived data
- E
Amazon S3 for archival storage and Amazon ElastiCache for low-latency transactional queries
Show answer and explanation
Correct answers: A, D
Explanation
Amazon S3 is an optimal choice for building a data lake due to its scalability, support for multiple data types, and integration with other AWS analytics services. For low-latency analytics, Amazon Redshift is a powerful solution for structured data. Additionally, Amazon Athena can be used to query archived data stored in S3, providing a cost-effective and serverless option for infrequent data access. This combination ensures both performance and cost-efficiency across different data access patterns.
- A. Correct.
Amazon S3 provides an ideal platform for building a data lake with support for storing structured, semi-structured, and unstructured data. Amazon Redshift complements this by providing a powerful, low-latency analytics solution for structured data.
- B. Incorrect.
Amazon RDS is a relational database designed for structured data. It does not scale well for unstructured or semi-structured data typically found in data lakes, making it unsuitable for this use case.
- C. Incorrect.
Amazon DynamoDB is a NoSQL database optimized for key-value and document-based workloads, not for storing or processing large-scale unstructured, semi-structured, or structured data typically found in data lakes.
- D. Correct.
Amazon S3 is a cost-effective and scalable solution for data lakes, while Amazon Athena enables serverless querying of data stored in S3, particularly useful for less frequently accessed archival data.
- E. Incorrect.
Amazon ElastiCache is optimized for in-memory caching and low-latency transactional queries but does not serve as a long-term data lake storage solution. Pairing it with S3 for archival storage does not meet the requirement of querying structured and semi-structured data.