This connector is set up by Kadoa. It is separate from direct S3 access through
the Cloud Storage connector.
Required Inputs
Choose the recipient mode that matches your environment.Databricks Recipient
Use this mode if you have a Unity Catalog-enabled Databricks workspace.| Input | Description |
|---|---|
| Sharing identifier | The Databricks sharing identifier for the workspace that should receive the share |
| Workflows | All workflows by default, or a selected workflow list |
| Activity log | Enabled by default, unless you ask Kadoa to disable it |
Token Recipient
Use this mode if you want to read the share with an open Delta Sharing client instead of a Databricks workspace.| Input | Description |
|---|---|
| Secure contact | The person or channel that should receive the one-time activation details |
| Workflows | All workflows by default, or a selected workflow list |
| Activity log | Enabled by default, unless you ask Kadoa to disable it |
Setup Flow
- Kadoa creates a Databricks connector for your team and selected workflows.
- Kadoa provisions a dedicated recipient, share, schema, and storage path.
- Kadoa verifies the provider-side share and grant setup before customer data is published.
- After each successful workflow run, Kadoa stages and validates public data, publishes Delta tables, and updates the share.
- For initial rollout, Kadoa publishes and verifies one live workflow delivery before running the full historical backfill.
Shared Tables
Each connector exposes physical Delta tables. Internal staging tables and raw provider tables are not shared.| Table | Purpose |
|---|---|
WF_<id>__V<n> | Versioned workflow output for a specific schema version |
WF_<id>__LATEST | Latest workflow output table for quick exploration |
| Workflow metadata tables | Workflow, schema version, and field mapping metadata |
ACTIVITY_LOG | Customer-visible activity events, when activity sharing is enabled |
_, are excluded before publish.
Schema Changes
Kadoa keeps historical schema versions available. When a workflow schema changes, Kadoa publishes a newWF_<id>__V<n> table and updates WF_<id>__LATEST only
after the version table and share checks pass. WF_<id>__LATEST follows the
newest validated schema; older rows remain available in their WF_<id>__V<n>
tables and metadata rows, and __LATEST may be rebuilt for the new schema.
Use versioned tables for downstream models that need a stable schema. Use
__LATEST for exploration or workloads that intentionally follow the newest
schema.