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Shopify to Apache Iceberg integration

Connect Shopify to Apache Iceberg and automatically sync your ecommerce platform data. Weld extracts Orders, Products, Customers, and Inventory from Shopify, loads them into Apache Iceberg, 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
Apache IcebergWarehouse
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
Apache IcebergDestinationApache IcebergReady
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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How it works

How to set up Shopify to Apache Iceberg 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 Apache Iceberg?
Ready for analysis.

Centralizing your Shopify data in Apache Iceberg 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 Apache Iceberg using SQL or your preferred BI tool.

  • Revenue and order analytics

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

  • Centralized data warehouse

    Bring Shopify data into Apache Iceberg 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 Apache Iceberg. 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 Apache Iceberg. 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 Apache Iceberg 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 Apache Iceberg.

Set up the MCP serverClaudeCursorChatGPTGemini
Claude CodeOpus 5
>

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

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 Apache Iceberg
>Ask about your Shopify data
Under the hood

Technical considerations.
What to expect.

Reverse ETL

ELT vs. reverse ETL: Shopify and Apache Iceberg

ELT (Extract, Load, Transform) moves data from Shopify into Apache Iceberg 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 Apache Iceberg 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 Apache Iceberg.

Apache Iceberg 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 Apache Iceberg 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

Apache Iceberg setup guide

How to connect Apache Iceberg 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 Apache Iceberg.

Start syncing Shopify to Apache Iceberg.

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

ShopifySource
WeldWeld
Apache IcebergWarehouse
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