SAP-C02 Question 222
Single answerA company is migrating its on-premises data analytics workload to AWS. The analytics workload involves processing large volumes of data stored in multiple formats, including Parquet and CSV, and running complex SQL queries. The company wants to minimize operational overhead, scale automatically based on the size of the data, and pay only for the queries run. Which service should the company choose?
- A
Amazon RDS for PostgreSQL
- B
Amazon EMR
- C
Amazon Redshift
- D
Amazon Athena
Show answer and explanation
Correct answer: D
Explanation
Amazon Athena is the optimal choice for this scenario because it meets the company's requirements for running SQL queries on data stored in multiple formats in Amazon S3, minimizing operational overhead, automatically scaling with data size, and using a pay-per-query pricing model. Other services like Amazon RDS, EMR, and Redshift are not as well-suited for these specific requirements due to their provisioning, management, or cost implications.
- A. Incorrect.
Amazon RDS for PostgreSQL is a managed relational database service, but it is not designed specifically for querying large-scale data stored in various formats like Parquet and CSV. Additionally, it requires provisioning and managing database instances, which increases operational overhead.
- B. Incorrect.
Amazon EMR is a scalable big data processing service, but it typically requires more configuration and management compared to serverless options. It is better suited for scenarios where custom big data frameworks like Apache Spark or Hadoop are required, rather than ad-hoc SQL querying.
- C. Incorrect.
Amazon Redshift is a fully managed data warehouse solution that can handle complex queries and analytics, but it requires provisioning clusters and is not as cost-effective for pay-per-query use cases. It is more suited for structured data in data warehouses rather than querying directly from S3.
- D. Correct.
Amazon Athena is a serverless query service that allows you to run SQL queries directly on data stored in Amazon S3 in formats like Parquet and CSV. It automatically scales based on the size of the data and charges only for the queries you run, making it the best fit for this scenario.