Supported data types
Inventory
Stock levels
Logistics
Shipping & fulfillment costs
Orders
Customer transactions
Product Attributes
Product metadata & descriptions
Returns
Returns, with or without an order reference
Prerequisites
Before setting up the Databricks integration, ensure you have:- A Databricks workspace with Delta Sharing enabled
- Tables in Unity Catalog containing your data, with columns matching our schema
- A share containing the relevant tables that can be shared externally
Alternative: Databricks-to-Databricks sharing
Alternative: Databricks-to-Databricks sharing
If your workspace uses Unity Catalog, you can share your tables with Dema’s Databricks workspace instead of sending an open Delta Sharing token. Contact your Customer Success Manager for Dema’s sharing identifier. Dema mounts your share as a catalog and reads
<catalog>.<schema>.<table> directly, so you don’t provide any bearer token or credentials.For incremental (changes) reads, enable Change Data Feed on the source table and add the table to the share with history. When Dema checks the connection, it confirms that the configured table is reachable.Instead of shareName, the table configuration uses the catalog name Dema mounted your share as:Connection
Each data type above is typically configured as its own integration, reading from its own table — set up as many or as few as you need, each pointed at its own
shareName/schema/table. There are two exceptions: the legacy Inventory V1 format combines stock levels and product attributes into a single table (see Version 1 (Legacy)), and returns can either use their own dedicated table (see Returns) or be recorded directly within the orders table (see Return fields within orders).Good to know
COGS priority
COGS priority
Storefront assignment
Storefront assignment
If you operate multiple storefronts, include
EXTERNAL_STOREFRONT_ID in your data for per-row storefront assignment.Merchant mappings
Step-by-step integration guide
1
Create a Delta Share
In your Databricks workspace, create a Delta Share containing the tables you want to integrate. Ensure the tables have columns matching our schema below.Refer to the Databricks Delta Sharing documentation for details on creating and managing shares.
2
Share credentials
Provide the following to your Customer Success Manager:Delta Sharing credentials:Table configuration:
Send the information via secure password sharing.
Credentials
Connection
3
Specifying data tables and schema
Ensure each table aligns with our schema. Columns must be named according to the column names specified in the schema below. This is crucial for accurate data integration.
4
Finalizing integration
After setting up the share and ensuring data mapping accuracy, our team will finalize the integration process, enabling data flow from Databricks into our platform.
Multiple values Some fields allow multiple values. These fields can be added as column of Array type, like
["value1", "value2", "value3"]. Data schema
Inventory
- Version 2 (Current)
- Version 1 (Legacy)
The current inventory format — only the stock-level and cost fields.
Fields
Fields
required
Logistics
Shipping and fulfillment costs associated with orders.Fields
Fields
Orders
Customer transaction data including order details and line items. See COGS priority for how cost values are resolved.How order data should be structured
How order data should be structured
Each row represents a unique order line, identified by the combination of
ORDER_ID, PRODUCT_ID, and VARIANT_NO.Order header fields
Order header fields
Required:
Order line fields
Order line fields
Required:
Return fields (within orders)
Return fields (within orders)
Include these fields to record returns directly in your orders table.Required:Optional:
Custom attributes
Custom attributes
Order header level:Order line level:
Product Attributes
Product metadata including names, categories, and descriptive attributes for your catalog.Required fields
Required fields
Optional fields
Optional fields
Custom attributes
Custom attributes
Returns
Return lines read from their own dedicated table. This is an alternative to the Return fields (within orders) accordion above — use whichever fits how your returns data is produced; you don’t need both. Each row is handled according to the identifier it carries: aRETURN_ID makes it an unreferenced return (even if the row also has an ORDER_ID), an ORDER_ID alone makes it a referenced return. Rows with neither are skipped. Both shapes can share one table.
- Referenced returns
- Unreferenced returns
Returns that link back to an existing order, which supplies the pricing.
Fields
Fields
Required:
Format:
Example:Optional:
required
Format:
Example:
Troubleshooting and support
For common issues and solutions, contact our support team directly for assistance.Additional resources
- Databricks Delta Sharing documentation: Databricks Documentation

