Amazon Athena

• An interactive query service that makes it easy to analyze data directly in S3 using standard SQL.

Features

• Athena is serverless.
• Has a built-in query editor.
• Uses Presto, an open source, distributed SQL query engine optimized for low latency, ad hoc analysis of data.
• Athena supports a wide variety of data formats such as CSV, JSON, ORC, Avro, or Parquet.
• Athena automatically executes queries in parallel, so that you get query results in seconds, even on large datasets.
• Athena uses Amazon S3 as its underlying data store, making your data highly available and durable.
• Athena integrates with Amazon QuickSight for easy data visualization.
• Athena integrates out-of-the-box with AWS Glue.

Athena uses a managed Data Catalog to store information and schemas about the databases and tables that you create for your data stored in S3.

Partitioning

• By partitioning your data, you can restrict the amount of data scanned by each query, thus improving performance and reducing cost.
• Athena leverages Hive for partitioning data.
• You can partition your data by any key.

Queries

• You can query geospatial data.
• You can query different kinds of logs as your datasets.
• Athena stores query results in S3.
• Athena retains query history for 45 days.
• Athena does not support user-defined functions, INSERT INTO statements, and stored procedures.
• Athena supports both simple data types such as INTEGER, DOUBLE, VARCHAR and complex data types such as MAPS, ARRAY and STRUCT.
• Athena supports querying data in Amazon S3 Requester Pays buckets.

Security

• Control access to your data by using IAM policies, access control lists, and S3 bucket policies.
• If the files in the target S3 bucket is encrypted, you can perform queries on the encrypted data itself.

Pricing

• You pay only for the queries that you run. You are charged based on the amount of data scanned by each query.
• You are not charged for failed queries.
• You can get significant cost savings and performance gains by compressing, partitioning, or converting your data to a columnar format, because each of those operations reduces the amount of data that Athena needs to scan to execute a query.

AWS Knowledge Center Videos: How do I analyze my S3 logs using Athena?

Note: If you are studying for the AWS Certified Data Analytics Specialty exam, we highly recommend that you take our AWS Certified Data Analytics – Specialty Practice Exams and read our Data Analytics Specialty exam study guide.

Sources:
https://docs.aws.amazon.com/athena/latest/ug/
https://aws.amazon.com/athena/features
https://aws.amazon.com/athena/pricing
https://aws.amazon.com/athena/faqs