Connect Amazon Athena

Your environment(s) must be on a supported release track to use the Amazon Athena connection.

Connect dbt to Amazon's Athena interactive query service to build your dbt project. The following are the required and optional fields for configuring the Athena connection:

Field	Option	Description	Type	Required?	Example
AWS region name	region_name	AWS region of your Athena instance	String	Required	eu-west-1
Database (catalog)	database	Specify the database (Data catalog) to build models into (lowercase only)	String	Required	awsdatacatalog
AWS S3 staging directory	s3_staging_dir	S3 location to store Athena query results and metadata	String	Required	s3://bucket/dbt/
Athena workgroup	work_group	Identifier of Athena workgroup	String	Optional	my-custom-workgroup
Athena Spark workgroup	spark_work_group	Identifier of Athena Spark workgroup for running Python models	String	Optional	my-spark-workgroup
AWS S3 data directory	s3_data_dir	Prefix for storing tables, if different from the connection's s3_staging_dir	String	Optional	s3://bucket2/dbt/
AWS S3 data naming convention	s3_data_naming	How to generate table paths in s3_data_dir	String	Optional	schema_table_unique
AWS S3 temp tables prefix	s3_tmp_table_dir	Prefix for storing temporary tables, if different from the connection's s3_data_dir	String	Optional	s3://bucket3/dbt/
Poll interval	poll_interval	Interval in seconds to use for polling the status of query results in Athena	Integer	Optional	5
Query retries	num_retries	Number of times to retry a failing query	Integer	Optional	3
Boto3 retries	num_boto3_retries	Number of times to retry boto3 requests (for example, deleting S3 files for materialized tables)	Integer	Optional	5
Iceberg retries	num_iceberg_retries	Number of times to retry iceberg commit queries to fix ICEBERG_COMMIT_ERROR	Integer	Optional	0

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Development credentials

Enter your development (not deployment) credentials with the following fields:

Field	Option	Description	Type	Required	Example
AWS Access Key ID	aws_access_key_id	Access key ID of the user performing requests	String	Required	AKIAIOSFODNN7EXAMPLE
AWS Secret Access Key	aws_secret_access_key	Secret access key of the user performing requests	String	Required	wJalrXUtnFEMI/K7MDENG/bPxRfiCYEXAMPLEKEY
Schema	schema	Specify the schema (Athena database) to build models into (lowercase only)	String	Required	dbt
Threads	threads		Integer	Optional	3

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Temporary credentials

If you prefer to not store long-lived IAM user AWS Access Key ID and AWS Secret Access Key in the dbt platform, you can use aws_session_token, which is part of temporary AWS Security Token Service (STS) credentials, instead. This approach mirrors a user or role’s long-term permissions.

To use temporary credentials:

1. Enter the AWS Access Key ID and AWS Secret Access Key in the development environment settings in the dbt platform user interface (UI).

2. Since the aws_session_token isn't available as a UI field in dbt platform, add it using Extended attributes in the environment settings or dbt platform profiles.

   When you set the aws_session_token in Extended attributes, the key is case-sensitive and must be exactly aws_session_token.

   For example, you can use an environment variable so the token isn't stored in the text box UI:

   aws_session_token: '{{ env_var(''DBT_ENV_AWS_SESSION_TOKEN'') }}'

3. Assign DBT_ENV_AWS_SESSION_TOKEN for each environment. Since temporary credentials expire, you need to refresh your STS credentials and update the environment (or the variable value) before expiration.

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