AWS-Athena

• Athena is an interactive query service that makes it easy to analyze data in Amazon S3 using standard SQL.

• Athena automatically executes queries in parallel, so that you get query results in seconds, even on large datasets

• It is serverless.

• 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 integrates out-of-the-box with AWS Glue.

• Athena integrates with Amazon QuickSight for easy data visualization.

• Users can use It to generate reports or to explore data with business intelligence tools or SQL clients, connected via an ODBC or JDBC driver.

• It can be accessed via the AWS Management Console, an API or an ODBC or JDBC driver.

• It can handle complex analysis, including large joins, window functions and arrays.

• User can invoke their SageMaker machine learning models in an Athena SQL query to run inference.

• With User-Defined Functions (UDFs), users can now write their own functions in Java and invoke them in Athena SQL query.

• Users can connect Athena to their external Apache Hive Metastore.

• It uses Apache Hive DDL to define tables.

• It supports compressed data in Snappy, Zlib, LZO and GZIP formats.

• It supports both simple data types such as INTEGER, DOUBLE, VARCHAR and complex data types such as MAPS, ARRAY and STRUCT.

• Users can run ANSI-Compliant SQL SELECT statements to query their data in Amazon S3.

• It uses SerDes (Serializer/Deserializer) to interpret the data read from Amazon S3.

• Parquet and ORC files created via Spark can be read in Athena.

• It allows users to partition their data on any column.

• It integrates with Amazon QuickSight, allowing users to easily visualize their data stored in Amazon S3.

• It has open sourced data source connectors to Apache HBase, Amazon DocumentDB, Amazon DynamoDB and Amazon CloudWatch Logs and CloudWatch Metrics.

• All Athena query results are stored in an Amazon S3 location that user set.

• It allows users to control access to their data by using AWS IAM policies, Access Control Lists (ACLs) and Amazon S3 bucket policies.

• It integrates with KMS and provides users an option to encrypt their result sets.

• It is priced per query and charges based on the amount of data scanned by the query.

• Users can save 30%-90% on their query costs and get better performance by compressing, partitioning & converting their data into columnar formats.

• Users are not charged for failed queries.

• If user cancel a query manually, they are charged for the amount of data scanned up to the point at which they cancelled the query.