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Use the data in your Amazon S3 table buckets in Wherobots. Connect a table bucket once from the Data Hub, then read and write its Iceberg tables from your Wherobots Spark workloads. Wherobots connects to Amazon S3 Tables through a Cloud Connection, which is a reusable IAM role that Wherobots assumes in your AWS account. The Data Hub wizard provisions everything with AWS CloudFormation, so there’s no IAM policy or Spark configuration to write by hand.

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Before you start

The following requirements must be met within both your Wherobots Organization and AWS account before you can connect to an S3 Tables catalog.
  • An Admin account within a Professional, Innovation, or Enterprise Edition Organization to create catalogs and Cloud Connections.
    Wherobots Organization members with the User role can use existing catalogs and Cloud Connections set up by Admins but cannot create new ones. See Organization Roles.
  • An existing Cloud Connection to your AWS account, or permission to create one. For more information, see Cloud Connections.
  • Your Organization ID, found at cloud.wherobots.com/organization.
  • An AWS account with an existing S3 table bucket. Unlike a general purpose S3 bucket, a table bucket stores Iceberg tables and manages their storage for you, so you don’t supply a separate S3 path.
  • The ARN of the table bucket you want to connect, in the form arn:aws:s3tables:<region>:<account-id>:bucket/<table-bucket-name>. Find it in the AWS console under S3 → Table buckets.
  • Permission to create CloudFormation stacks that provision IAM resources (typically AdministratorAccess), so Wherobots can set up the Cloud Connection and grant it S3 Tables access. CloudFormation creates the IAM role and policies for you, so you don’t edit them by hand.
    The pre-filled templates create or modify IAM resources on your behalf. The actions they perform typically require AdministratorAccess:For a complete list of IAM Actions, see Actions defined by AWS Identity and Access Management in the AWS Documentation.

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Cloud Connections

Before you can connect to an Amazon S3 Tables catalog, Wherobots needs a Cloud Connection to your AWS account.
A Cloud Connection is a single, reusable trust relationship between your Wherobots Organization and a cloud provider account. For AWS, it’s a first-class object that stores your AWS account ID and an IAM role (with an external ID) that Wherobots assumes on your behalf to access resources in your account.
Create one Cloud Connection per AWS account and reuse it across all of your S3 storage integrations and AWS Glue catalogs in that account, instead of configuring credentials separately for each one.
Trust is established with AWS CloudFormation. Create the connection directly in the Wherobots UI, or download the CloudFormation template (YAML) so your security team can review it before deploying.

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Manage Cloud Connections

Cloud Connections live in Organization Settings under Cloud Connections, where Admins can create, list, verify, and delete them.
  • Verify: Confirms Wherobots can assume your IAM role through the two-hop AWS STS AssumeRole chain.
  • Delete: Blocked while any storage integration or Glue catalog is still bound to the connection. You must remove any resources bound to that Cloud Connection prior to its deletion.

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Connect to the Amazon S3 Tables catalog

Connect your S3 table bucket to your Wherobots Organization in order to read and write to it from your Wherobots workloads. The Data Hub wizard provisions the connection with a CloudFormation stack, so you don’t have to write IAM policies or Spark configs by hand.
1

Open the Add Amazon S3 Tables Catalog wizard

In Wherobots Cloud, open the Data Hub.With no catalog selected, the details pane shows Add data cards. Select the Amazon S3 Tables card.
The Data Hub empty state showing the Unity Catalog, Amazon Glue, and Amazon S3 Tables cards

Data Hub add data cards: Unity Catalog, Amazon Glue, and Amazon S3 Tables.

This opens the Add Amazon S3 Tables Catalog wizard.
2

Enter the catalog details

On the Details step, enter:
  • Name: The name of the catalog in Wherobots.
    • This affects the Fully Qualified Name (FQN) used to reference this catalog in Wherobots: CATALOG_NAME.DATABASE_NAME.TABLE_NAME, where DATABASE_NAME is the S3 Tables namespace.
    • A name can contain any character. But if it includes anything other than letters, numbers, or underscores — such as a space, dash, or period — you must wrap the name in backticks wherever you reference it in the FQN. For example, a catalog named My-Catalog is referenced as `My-Catalog`.namespace.table.
    For simplicity and to avoid quoting issues, it’s recommended to use only alphanumeric characters or underscores.
  • Table Bucket ARN: The ARN of the S3 table bucket you’re connecting, for example arn:aws:s3tables:us-east-1:123456789012:bucket/my-table-bucket. The region and AWS account are read from the ARN, so there’s no separate AWS Region or S3 Path field to fill in.
  • Access level: The level of access Wherobots has to the catalog.
    • Choose Read-only to allow Wherobots to read tables in your S3 Tables catalog, but not create or modify them.
    • Choose Read-write to allow Wherobots to read, create, and modify tables in your S3 Tables catalog.
  • Click Continue.
The Details step of the Add Amazon S3 Tables Catalog wizard

Step 1, Details: name the catalog, then set the table bucket ARN and access level.

3

Choose a Cloud Connection

On the Connection step, pick an existing Cloud Connection or create a new one, then click Continue.

Create a new Cloud Connection

Creating a connection takes two steps inside the Create Cloud Connection dialog.
1

Enter the connection details

  • Connection Name — a label that identifies the trust relationship in Wherobots.
  • AWS Account ID — the 12-digit AWS account you’re connecting to.
Click Create Connection.
The Create Cloud Connection dialog

Connection details: name the connection and enter your AWS Account ID.

2

Grant access in AWS

Wherobots generates a pre-filled CloudFormation stack that creates the connection’s IAM role. Click Open in AWS Console to launch it in a new tab, or Download Template to run it yourself.
The Grant access in AWS step of the Create Cloud Connection dialog, with Open in AWS Console and Download Template buttons

Grant access in AWS: launch the pre-filled CloudFormation stack that creates the Cloud Connection role.

On the AWS Quick create stack page, everything is pre-filled. Scroll to the bottom, select I acknowledge that AWS CloudFormation might create IAM resources, and click Create stack.
The Capabilities section of the AWS Quick create stack page with the IAM acknowledgment checkbox selected

On the AWS Quick create stack page, acknowledge the IAM capability and click Create stack.

Back in Wherobots, click Done to finish creating the connection.
4

Deploy the catalog stack

On the Deploy step, launch the pre-filled CloudFormation stack. It attaches S3 Tables access to your Cloud Connection.Wherobots displays the Stack name it uses, so you can find the stack later in the AWS CloudFormation console.
  1. Click Open in AWS Console (or Download Template to manually paste it into the AWS CloudFormation console).
  2. On the AWS Quick create stack page, scroll to the bottom, select I acknowledge that AWS CloudFormation might create IAM resources, and click Create stack.
  3. Return to Wherobots and click Create catalog.
Create catalog stays disabled until you launch the stack or download the template.
The Deploy step of the Add Amazon S3 Tables Catalog wizard, showing the stack name, the Open in AWS Console and Download Template buttons, and a disabled Create catalog button

Step 3, Deploy: launch the pre-filled CloudFormation stack, then return to Wherobots to create the catalog.

Expand What to do on the AWS page for an annotated walkthrough of the AWS Quick create stack page.
The expanded What to do on the AWS page section, showing an annotated AWS console screenshot that marks the IAM acknowledgement checkbox and the Create stack button

Step 3, Deploy, with What to do on the AWS page expanded.

5

Verify and finish

After the stack completes, Wherobots verifies it can access your table bucket. Once verified, the catalog appears in the Data Hub and is ready to use.
IAM changes can take a few minutes to propagate across AWS. If verification fails immediately, wait a moment and retry.

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Next Steps

After you connect your S3 Tables catalog, you can query its tables from a Wherobots notebook. See Query Amazon S3 Tables Catalog in a Notebook for guidance and starter code.
Runtime Restart Required After Data IntegrationTo use new storage integrations or catalogs in your notebooks, you must start a new runtime. Notebooks can only access storage integrations or catalogs that were created before the runtime started.

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Limitations

Review the following caveats of the s3 tables integration:
  • S3 tables integration doesn’t support staged creates.
    • CREATE TABLE AS SELECT (CTAS) / REPLACE TABLE AS SELECT (RTAS) unsupported as S3 Tables rejects staged creates and will output "Stage-create is currently not supported" if attempted.
  • S3 tables integration doesn’t support reading or writing views.
  • S3 tables integration doesn’t support ALTER TABLE … RENAME TO.
  • Iceberg V3 Tables can be read, but ONLY if they don’t have any of the new column types (geometry / geography, variant, timestamp_ns).
  • Geometry round-trips as WKB binary is not supported.
    • geometry columns are read back as binary and require use of ST_GeomFromWKB().
  • DROP TABLE / DROP NAMESPACE from Spark is unsupported.