SAA-C03 · Question #331
A company runs an online order management system on AWS. The company stores order and inventory data for the previous 5 years in an Amazon Aurora MySQL database. The company deletes inventory data aft
The correct answer is B. Use the SELECT INTO OUTFILE S3 query on the Aurora database to export the data to Amazon. Amazon Aurora MySQL supports the SELECT INTO OUTFILE S3 SQL syntax to export query results directly to Amazon S3. This is an efficient and low-overhead method for archiving data. Once data is in S3, Lifecycle rules can be configured to automatically transition older data to lower
Question
A company runs an online order management system on AWS. The company stores order and inventory data for the previous 5 years in an Amazon Aurora MySQL database. The company deletes inventory data after 5 years. The company wants to optimize costs to archive data. Which solution will meet this requirement?
Options
- ACreate an AWS Glue crawler to export data to Amazon S3. Create an AWS Lambda function to
- BUse the SELECT INTO OUTFILE S3 query on the Aurora database to export the data to Amazon
- CCreate an AWS Glue DataBrew job to migrate data from Aurora to Amazon S3. Configure S3
- DUse the AWS Schema Conversion Tool (AWS SCT) to replicate data from Aurora to Amazon S3.
How the community answered
(41 responses)- A7% (3)
- B73% (30)
- C2% (1)
- D17% (7)
Explanation
Amazon Aurora MySQL supports the SELECT INTO OUTFILE S3 SQL syntax to export query results directly to Amazon S3. This is an efficient and low-overhead method for archiving data. Once data is in S3, Lifecycle rules can be configured to automatically transition older data to lower-cost storage classes (such as S3 Glacier) or delete it after a defined period, providing a cost-optimized and automated archive solution. The Glue-based options involve more services and operational overhead. SCT is intended for database migrations, not for periodic data archival.
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