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Shopify to Databricks integration

Connect Shopify to Databricks and automatically sync your ecommerce platform data. Weld extracts Orders, Products, Customers, and Inventory from Shopify, loads them into Databricks, and lets you transform the data using SQL or dbt, no custom scripts required.

Start for freeView setup guide
4.8 on G2
ShopifySource
WeldWeld
DatabricksWarehouse
Weld · New sync
ShopifySourceShopifyConnected
Tables to sync
  • order137 cols
  • product14 cols
  • customer26 cols
  • location21 cols
  • fulfillment_event23 cols
  • product_variant26 cols
  • Extract
  • Load
  • Keep in sync
DatabricksDestinationDatabricksReady
shopify schema
  • shopify.orderSynced
  • shopify.productSyncing
  • shopify.customerSynced
  • shopify.locationSynced
  • shopify.fulfillment_eventSynced
  • shopify.product_variantSynced
Shopify tables
92
fields, typed
1,450
relationships kept
54
agent context included
MCP

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  • Flatpay
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  • Danish Endurance
  • Female Invest
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  • Pas Normal Studios
How it works

How to set up Shopify to Databricks in Weld.
In the app, with the API or an agent.

Setup guideAPI guideMCP docs
Weld · New Shopify sync
ShopifyNew connectionShopifyAuthorised
Connection nameshopify
AuthorizeOpens Shopify to grant read access
Use cases

Why sync Shopify to Databricks?
Ready for analysis.

Centralizing your Shopify data in Databricks lets you join it with other data sources for cross-platform analytics and deeper insights.

Build reliable dashboards and reports by querying Shopify data directly in Databricks using SQL or your preferred BI tool.

  • Revenue and order analytics

    Track orders, products, and customer behavior from Shopify in Databricks. Build cohort analyses, LTV models, and inventory forecasting.

  • Centralized data warehouse

    Bring Shopify data into Databricks alongside other sources to create a single source of truth for your organization.

  • Automated reporting

    Replace manual exports and spreadsheet-based reporting with automated pipelines from Shopify to Databricks. Connect BI tools like Looker, Metabase, or Power BI.

Schema

What data can you sync?
Every Shopify table, keys intact.

Weld syncs the following data objects from Shopify into Databricks. The exact tables and fields depend on your Shopify configuration and the permissions granted during setup.

Open the schema explorer
All 92 tables
  • order
  • product
  • customer
  • location
  • fulfillment_event
  • product_variant
  • fulfillment_order
  • inventory_item
  • draft_order
  • shop
  • fulfillment
  • collection
  • inventory_level
  • product_variant_contextual_pricing
  • inventory_level_quantities
  • abandoned_checkout
  • transaction
  • abandoned_checkout_line
  • order_agreement_sale
  • order_line
  • draft_order_line
  • price_rule
  • fulfillment_order_line
  • order_line_refund
  • order_customer_journey_summary_visit
  • discount_code
  • order_metafield
  • transaction_fees
  • payment_dispute
  • company_contact
  • and 62 more
Weld MCP server

Ask your agent.
It queries Databricks for you.

Connect Claude, Cursor, ChatGPT or your own agent to Weld over MCP. It reads the Shopify context, finds the tables it needs and runs the query in Databricks.

Set up the MCP serverClaudeCursorChatGPTGemini
Claude CodeOpus 5
>

How many order rows do we have per customer? Use our Shopify data in Databricks.

Reading the Shopify context first, so the query uses the right tables and keys.

●weld·search_available_references
⎿raw.shopify.order
raw.shopify.customer
+ 90 more Shopify tables
●weld·get_reference_schema
⎿order · 137 columns
joins customer on customer_id
●weld·run_query
⎿select c.id, count(*) from {{raw.shopify.order}} o
join {{raw.shopify.customer}} c on o.customer_id = c.id
group by 1
submitted
●weld·get_query_status
⎿DONE
●weld·get_query_result
⎿rows returned
✓Answered from Shopify data in Databricks
>Ask about your Shopify data
Under the hood

Technical considerations.
What to expect.

Reverse ETL

ELT vs. reverse ETL: Shopify and Databricks

ELT (Extract, Load, Transform) moves data from Shopify into Databricks for analysis. This is the approach shown on this page, and the one to use for dashboards, reports, and data models.

Reverse ETL works the other direction: it pushes enriched data from Databricks back into Shopify. For example, you could sync computed lead scores or customer segments from your warehouse into Shopify to personalize outreach.

Weld supports both directions, so you can build a complete data loop between Shopify and Databricks.

Databricks to Shopify
Incremental syncing
Weld uses incremental syncing where supported by the Shopify API, loading only new and updated records to minimize data transfer and warehouse costs.
Schema handling
Weld automatically manages schema changes. If Shopify adds new fields, they're detected and added to the corresponding Databricks tables.
Data freshness
Sync frequency depends on your Weld plan. Most connectors support schedules from every 5 minutes up to daily intervals.
Security
All data is encrypted in transit (TLS) and at rest. Weld is SOC 2 Type II compliant and supports IP whitelisting for database connections.
Resources

Keep reading.
Guides, docs and schema.

Documentation

Shopify setup guide

How to connect Shopify to Weld, step by step.

Documentation

Databricks setup guide

How to connect Databricks to Weld, step by step.

Schema

Shopify schema explorer

Browse all 92 tables and 1,450 fields.

Connector

Shopify connector

Everything Weld does with Shopify.

FAQ

Common questions.
About Shopify to Databricks.

Start syncing Shopify to Databricks.

Set up your Shopify data pipeline in minutes. No credit card required. Free for 14 days.

ShopifySource
WeldWeld
DatabricksWarehouse
Start for freeTalk to us
Related

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