> For the complete documentation index, see [llms.txt](https://docs.e6data.com/query-engine/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.e6data.com/query-engine/guides/deployment/aws-in-vpc/register-catalog.md).

# Register catalog

Grant the In-VPC engine access to your data lake and register a catalog in your e6data workspace.

With the workspace deployed, connect your data so you can query it. This has two parts: granting the engine access to your data lake, and registering a catalog in the Compute Plane.

## Grant data-lake access

The In-VPC engine reads your data through IAM. To grant access to data lakes in your account (or in another account), create the cross-account IAM role, S3 read policy, and - if you use Glue - the Glue catalog access policy. These are the same policies used for a Serverless deployment; see [Configure AWS access](/query-engine/guides/deployment/aws-serverless/configure-aws-access.md) for the full role, trust policy, and S3/Glue policy definitions.

The workspace **engine role** already includes `sts:AssumeRole` and `sts:TagSession`, so it can assume a cross-account role you create for data access.

## Register the catalog

1. Open the workspace's Compute Plane and go to the **Catalogs** section.
2. Select **Create Catalog** and choose your **Catalog Type** - AWS Glue, Hive Metastore, Databricks Unity, Apache Polaris, Iceberg REST, or Amazon S3 Tables.
3. Provide the connection details and, where your data is in another account, the **Target AWS Account ID** and **IAM Role ARN**.
4. Select **Test Connection**, choose the schemas to include, and select **Create Catalog**.

For the full set of catalog types and their connection settings, see [Catalogs](/query-engine/guides/catalogs.md).

## Next

Continue to [Create a cluster](/query-engine/guides/deployment/aws-in-vpc/create-cluster.md).


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