Skip to main content

​
Supported data types

Inventory

Stock levels & product data

Orders

Customer transactions

Product Attributes

Product metadata & descriptions

​
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

​
Good to know

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:
Send the information via secure password sharing.
  "bearerToken": "<your-token>",
  "endpoint": "https://<workspace-url>/api/2.0/delta-sharing",
  "shareName": "example_share",
  "schema": "example_schema",
  "table": "example_table",

  // optional
  "icebergEndpoint": "https://<workspace-url>/api/2.0/unity-catalog/iceberg",
  "expirationTime": "2026-12-31T23:59:59.999Z"
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

Stock levels across your warehouses. Product metadata (name, brand, category, etc.) is sent separately via Product Attributes. See COGS priority for how cost values are resolved.
The current inventory format. Contains only stock-level and cost fields. Product attributes (name, brand, category, etc.) are sent separately via the Product Attributes data type.

Fields

required



​
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

Each row represents a unique order line, identified by the combination of ORDER_ID, PRODUCT_ID, and VARIANT_NO.
RequirementDescription
Unique rowsEach row must have a unique ORDER_ID-PRODUCT_ID-VARIANT_NO combination
Quantity handlingIf multiple items of the same variant were bought, aggregate them using QUANTITY_DECIMAL
Tax inclusionAll prices should include tax
Header repetitionOrder header fields (like ORDER_ID, CURRENCY, TOTAL) must be repeated for every line item in the same order
UpdatesWhen an order changes, update the existing rows for that ORDER_ID in place and set UPDATED_AT to the current timestamp. Do not insert duplicate rows — each ORDER_ID–PRODUCT_ID–VARIANT_NO combination must remain unique
Storefront mappingTo map data to a specific storefront, fill out EXTERNAL_STOREFRONT_ID and provide us with info about your existing storefronts, see Storefront assignment
Required:
Required:
Include these fields to record returns directly in your orders table.

​
Product Attributes

Product metadata including names, categories, and descriptive attributes for your catalog.

Required fields

​
Troubleshooting and support

For common issues and solutions, contact our support team directly for assistance.

​
Additional resources