Serverless SQL queries directly against data stored in Amazon S3
Amazon Athena is a serverless query service that runs SQL against data sitting in Amazon S3 or other supported sources. There is no cluster to size or maintain: you point a table definition at a prefix, and Athena queries the files directly, including CSV, JSON, Parquet, ORC and Avro. It is built on a Trino and Presto lineage, so familiar SQL works, and integration with the Glue Data Catalog means tables can be shared with other AWS analytics services. Billing is per query by data scanned, which makes Parquet partitioning and compression an economic decision rather than just a performance one.
Last updated: 2026-09-20. This site only provides an index; for exact features, pricing, and licensing, see the official website.
log analysis, ad hoc s3 querying, data lake exploration and cost-aware reporting
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Athena bills by bytes scanned, so a query against a daily partition costs far less than one scanning a year of files. Converting to Parquet with partitions and selecting only needed columns can cut a bill by an order of magnitude.
No. It is a conventional SQL engine over object storage. Machine learning work would use services such as SageMaker or Athena's Spark integrations for feature engineering before training elsewhere.
When many users run concurrent dashboards, when workloads need consistently fast interactive response, or when complex joins repeat constantly. Athena suits ad hoc exploration and log analysis where infrastructure-free operation matters more.
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