Athena uses Apache Hive to define tables and create databases, which are essentially a logical namespace of tables

Schema on Read

You can run DDL statements in the Athena console, using a JDBC or an ODBC driver, or using the Athena Create Table wizard.

You can find guidance for how to create databases and tables using Apache Hive documentation

Just like you run a create table in a regular SQL query tool on any database such as MySQL, Oracle, or SQL Server Manager

When you query an existing table, under the hood, Amazon Athena uses Presto, a distributed SQL engine

When you create tables and databases manually, Athena uses HiveQL data definition language (DDL) statements such as CREATE TABLE, CREATE DATABASE, and DROP TABLE under the hood to create tables and databases in the AWS Glue Data Catalog, or in its internal data catalog in those regions where AWS Glue is not available.

To improve query performance and reduce costs, we recommend that you partition your data and use open source columnar formats for storage in Amazon S3, such as Apache Parquet or ORC.

To create a table with partitions, you must define it during the CREATE TABLE statement. Use PARTITIONED BY to define the keys by which to partition data