Key points

• Query cost and performance depend heavily on scanned data, so use columnar formats, compression, and partition pruning.
• Athena separates query compute from S3 storage and avoids operating a warehouse for intermittent analysis.
• Catalog permissions, S3 access, and KMS access must all permit the query path.

Best-known use cases

• Ad hoc SQL over data-lake objects.
• Occasional analytics where managed infrastructure and fast setup matter.

What candidates often confuse it with

• Athena queries S3 in place; Amazon Redshift is a managed data warehouse for sustained analytical workloads.
• AWS Glue catalogs and transforms data; Athena runs SQL queries against cataloged datasets.

Key takeaway

Choose Athena when SQL must query S3 data without provisioning a database or cluster.

Related services

• Amazon S3
• AWS Glue
• AWS Lake Formation
• Amazon Redshift

Relevant exam tasks

• D3.5

Learn more

• Amazon Athena