Querying metadata tables with AWS analytics services
Note
The S3 Metadata feature is in preview release for Amazon S3 and is subject to change.
You can query your S3 managed metadata tables with AWS analytics services such as Amazon Athena, Amazon Redshift, and Amazon EMR.
Before you can run queries, you must first integrate the S3 table buckets in your AWS account and Region with AWS analytics services.
Note
Integrating S3 table buckets with AWS analytics services is in preview release and subject to change.
Querying metadata tables with Amazon Athena
After you integrate your S3 table
buckets with AWS analytics services, you can start querying your metadata tables
in Athena. In your queries, specify your catalog as s3tablescatalog and your
database as aws_s3_metadata (which is the namespace for your metadata tables).
For more information, see Querying Amazon S3 tables
with Athena.
Querying metadata tables with Amazon Redshift
After you integrate your S3 table
buckets with AWS analytics services, you create
a resource link to your metadata table namespace (aws_s3_metadata).
Once that's done, you can start querying your metadata tables in the Amazon Redshift console. For
more information, see Accessing Amazon S3 tables
with Amazon Redshift.
Querying metadata tables with Amazon EMR
To query your metadata tables by using Amazon EMR, you create an Amazon EMR cluster configured for Apache Iceberg and connect to your metadata tables using Apache Spark. You can set this up by integrating your S3 table buckets with AWS analytics services or using the open-source Amazon S3 Tables Catalog for Iceberg client catalog.
For more information, see Accessing Amazon S3 tables with Amazon EMR.
