SAA-C03 Question 223
Single answerA data analytics company processes petabytes of log data daily and requires a scalable storage solution for their data lake. They need a cost-effective service that can handle large-scale storage, provide high availability, and integrate with their analytics tools for optimized query performance. Which AWS storage solution is the most appropriate for their requirements?
- A
Amazon S3 with S3 Standard storage class
- B
Amazon EFS (Elastic File System)
- C
Amazon RDS with a General Purpose SSD storage
- D
Amazon DynamoDB
Show answer and explanation
Correct answer: A
Explanation
Amazon S3 with S3 Standard is the most suitable option for building a data lake due to its scalability, durability, and cost-effectiveness. It supports massive amounts of unstructured data and integrates well with analytics tools, addressing the company's need for high availability and optimized query performance. Other options like EFS, RDS, and DynamoDB are designed for different use cases and do not align with the petabyte-scale data lake requirement.
- A. Correct.
Amazon S3 with S3 Standard is the best choice because it is a highly scalable, durable, and cost-effective object storage service ideal for data lakes. It integrates seamlessly with analytics tools like Amazon Athena and AWS Glue, making it perfect for the described use case.
- B. Incorrect.
Amazon EFS is a scalable file storage solution, but it is designed for use cases requiring file system semantics, such as shared file storage for applications, and is not ideal for a data lake with petabyte-scale storage needs.
- C. Incorrect.
Amazon RDS is a managed relational database service and is not suitable for large-scale, unstructured data storage like a data lake. It is designed for structured data in a database format, which doesn't align with the scenario.
- D. Incorrect.
Amazon DynamoDB is a NoSQL database service designed for high-performance, low-latency key-value or document-based workloads. It is not suitable for storing petabytes of log data or creating a data lake.