Data structure for Reltio Data Sharing with Databricks
Learn how Reltio structures its catalog, schemas, and tables to support Delta Sharing with Databricks.
When using Delta Sharing to share Reltio data with Databricks, Reltio organizes the output into a structured catalog and schema pattern. This pattern includes a predictable set of dynamic tables tailored to your tenant configuration. The schema supports flattened views or full hierarchy for complete data fidelity and for AI and analytics use cases.
Catalog and schema naming
Reltio creates a dedicated catalog and schema per tenant and adapter. This ensures data is isolated by context and can be accessed securely in Databricks Unity Catalog.
| Component | Naming convention |
|---|---|
| Data Share Provider | reltio |
| Catalog | reltio_datashare_{tenantId} |
| Schema |
reltio_datashare_{adapterName}
|
Types of tables
Each schema for OV only mode and non-OV only mode includes different sets of tables optimized for specific stages of data consumption.
These tables represent final, structured outputs for predefined object types.
matchesmergeslinksworkflowsactivities
Created dynamically based on the tenant's business model, these tables provide flattened views of entities, relationships, and interactions for OV only mode. If the share is created without OV, the tables are still generated, but use hierarchical structure instead of a flattened schema.
Entity tables
- Format:
entity_{entityTypeShortUri} - Examples:
entity_Individual,entity_Organization
Relationship tables
- Format:
relation_{relationshipTypeShortUri} - Examples:
relation_Owns,relation_Manages
Interaction tables
- Format:
interaction_{interactionTypeShortUri} - Examples:
interaction_Email,interaction_Call