Shopify connector

Important

This feature is in Beta. To use it, a workspace admin must turn on Lakeflow Connect for Shopify from the Previews page. See Manage Azure Databricks previews.

The managed Shopify connector in Lakeflow Connect ingests e-commerce data such as products, orders, customers, inventory, fulfillments, and discounts from Shopify into Azure Databricks. It also captures deletions of products, product variants, collections, articles, pages, blogs, and draft orders.

Feature availability

Feature	Availability
UI-based pipeline authoring	Supported
API-based pipeline authoring	Supported
Declarative Automation Bundles	Supported
Incremental ingestion	Supported
Unity Catalog governance	Supported
Orchestration using Databricks Workflows	Supported
API-based column selection and deselection	Supported
API-based row filtering	Not supported
SCD Type 2	Supported Tables with semi-structured (VARIANT) columns don't support SCD type 2.
Automated schema evolution: New and deleted columns	Supported
Automated schema evolution: Data type changes	Not supported
Automated schema evolution: Column renames	Not supported Requires a full refresh.

Authentication methods

Authentication method	Availability
OAuth U2M	Not supported
OAuth M2M	Supported OAuth client credentials from a Shopify app.
Basic authentication (username/password)	Not supported

Ingest from Shopify in 3 steps

Note

Before starting, review the Azure Databricks user persona, supported interfaces, ingestion frequency, and common patterns.

Start ingesting from Shopify

1. Configure Shopify for ingestion (Admins): Set up Shopify to authenticate with Azure Databricks.
2. Create a Unity Catalog connection (Admins): Create a connection in Catalog Explorer so non-admins can create pipelines.
3. Create an ingestion pipeline (Admins or non-admins): Select any supported interface and create a pipeline from an existing connection.