Frequently used aggregates remain in Redshift while long-term raw data stays in S3.
Join the S3 data with local Redshift tables using SQL.
Which approach is most appropriate?
Define an external schema and tables for Redshift Spectrum, using Catalog metadata and least-privilege access.
Detailed explanation
Audit logs do not become queryable external tables.
Audit logs do not become queryable external tables.
Lifecycle manages object retention and transitions, not table definitions.
Lifecycle manages object retention and transitions, not table definitions.
Spectrum lets Redshift SQL read S3 data and join it with local tables.
Spectrum lets Redshift SQL read S3 data and join it with local tables.
DynamoDB Scan reads DynamoDB items, not S3 objects.
DynamoDB Scan reads DynamoDB items, not S3 objects.
Check official documentation
Compare the following points with the official documentation.
Amazon Redshift Spectrum、external schema、S3、Glue Data Catalogの公式説明を確認する。
What to confirm
S3外部表とRedshift内部表の役割を説明できる。
Key points
- Redshift Spectrum
- External schema
- S3
- Glue Data Catalog
Notes
- Environment: AWS公式DEA-C01試験ガイドと各サービスの公式ドキュメントの確認
- Confirm current AWS service behavior in the official DEA-C01 documentation.
Foundation review
Storage tiering
Keep frequent data local and long-term raw data in S3 when cost and latency permit.
Cross-service permissions
The Redshift role, Catalog grants, and S3 policy must all allow the read.