DEA-C01 Question 154
Single answerA retail company processes incoming transactional data from their point-of-sale systems in real-time. They want to store this data for analytics and reporting. The data must be queryable with SQL-like syntax, and the solution should be cost-effective for large amounts of data. Which data store should they use?
- A
Amazon RDS
- B
Amazon Redshift
- C
Amazon S3 with Amazon Athena
- D
Amazon DynamoDB
Show answer and explanation
Correct answer: C
Explanation
Amazon S3 with Amazon Athena is the best choice for this scenario because it combines the scalability and cost-effectiveness of Amazon S3 for data storage with the ability to run SQL-like queries using Amazon Athena. This approach is ideal for large-scale data that needs to be analyzed without the overhead of maintaining a traditional data warehouse or relational database system.
- A. Incorrect.
Amazon RDS is a managed relational database service but is not the most cost-effective option for large-scale data storage and analytics. It is better suited for OLTP workloads rather than large-scale analytics.
- B. Incorrect.
Amazon Redshift is a powerful data warehouse solution for analytics, but it might not be the most cost-effective option for storing raw data at large scale, especially if the data is queried infrequently.
- C. Correct.
Amazon S3 with Amazon Athena is a cost-effective solution for storing large amounts of data in Amazon S3 and querying it using SQL-like syntax via Athena. This is well-suited for the given scenario.
- D. Incorrect.
Amazon DynamoDB is a NoSQL database designed for key-value and document-based workloads. It does not natively support SQL-like queries, making it unsuitable for this use case.