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CRM / Data warehouse · Two-way sync platform

Shopify and Snowflake integration — two-way sync

Keep supported Shopify and Snowflake records aligned with two-way sync. Give each team access to current data while controlling which system can update each field.

  • Field mappings and sync direction under your control
  • Inspect and resolve record errors in one dashboard
Two-way sync for supported objects
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Shopify
Snowflake
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Example workflow

Sales order reporting workflow

Object-specific availability and field permissions determine this mapping. Use the restrictions shown for each record type.

Starting eventA change involving Shopify Orders or the proposed sales order table in Snowflake needs a defined result in the other system.

  1. Start with Shopify Orders and the proposed sales order table in Snowflake. Use the record-matching and field-ownership rules from your mapping worksheet.

  2. Create or locate the customer and products first; resolve taxes, currency, and fulfillment references.

  3. Test a normal update and one failed or repeated update in the supported direction. Keep both record IDs with the test results.

What to verifyTest a multi-line order, a partial cancellation, and two partial shipments. Compare line totals as well as the header.

Review records and field ownership

Mapping essentials

Records and field ownership

Match records by stable IDs and assign an owner for each field. The record notes identify the coverage to check.

Download the mapping worksheet

CSV · No email required

Example record relationships between Shopify and Snowflake
Shopify recordSnowflake recordRecord matchingField ownership
OrdersDocumented record: SupportedReporting datasetProposed sales order tableProposed table; choose its name and schema.Preserve both the order ID and stable line IDs. Allow one order to relate to several shipments or invoices.Decide which system approves the order and which can cancel or amend it after fulfillment begins.
ProductsDocumented record: SupportedReporting datasetProposed product or catalog item tableProposed table; choose its name and schema.Distinguish the product ID, variant ID, SKU, and price-list entry; they are not interchangeable keys.Assign ownership for catalog content, price, and stock separately.
ProductVariantsDocumented record: SupportedReporting datasetProposed product variant tableProposed table; choose its name and schema.Retain variant ID separately from parent-product ID and SKU; a product with several variants must keep several identities.Choose who owns variant definitions, prices, and availability; they may have different sources.

Use writable fields from the connected accounts. Read values from read-only fields without writing changes back to them, and define deletion handling separately.

Why teams connect Shopify and Snowflake

Put your Shopify and Snowflake data to work

Start with the work your team needs to complete: keep records up to date, make operational data available for reporting, or move data to a new system. Choose one Shopify and Snowflake workflow to test, define what success looks like, and decide who handles failed updates.

  • Sync orders, customers, and inventory into Postgres for operational reporting across stores.

  • Keep customer records aligned between Shopify and a CRM for segmentation and lifetime-value analysis.

  • Land CRM and ERP records in Snowflake continuously so BI reflects business systems without nightly batch ETL

  • Activate modeled Snowflake tables by syncing scores and attributes back into CRM fields sales can act on

What records can you sync?

Start with the records your workflow needs. Check each system’s read and write requirements before mapping fields.

Shopify

Read and write support varies by record

Record types covered in the setup guide

Record typesCoverage and requirements
  • Products
  • ProductMedias
  • ProductVariants
  • Orders
  • Customers
  • Abandoned Checkouts
✅ Supported. Confirm field permissions and sync direction.

Read the Shopify connector guide

Snowflake

Read and write support varies by record

Record types covered in the setup guide

Record typesCoverage and requirements
  • Standard tables (including Permanent, Transient and Temporary tables)
✅ Supported. Confirm field permissions and sync direction.
  • Views (including materialized and non-materialized views)
🕘 Coming soon. Confirm field permissions and sync direction.
  • External tables
❌ Not supported. Confirm field permissions and sync direction.

Read the Snowflake connector guide

Connection essentials

Review how each system connects, detects changes, and permits access to your records.

View setup requirements and limits
Connection requirementShopifySnowflake
Integration interfaceGraphQL Admin API (primary) and REST Admin API (legacy)SQL via JDBC/ODBC and native drivers, plus the Snowflake SQL REST API
AuthenticationOAuth via a custom Shopify appDedicated Snowflake service user + role with RSA key-pair authentication
Change detectionThe saved Stacksync guide does not specify the change-detection mechanism.The saved Stacksync guide does not specify the change-detection mechanism.
Read accessAvailable for supported recordsAvailable for supported records
Write accessAvailable for supported recordsAvailable for supported records

Enterprise controls

Security and control for your integrations

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Compliance and data transfers

As a data company, we understand the importance of keeping your data secure. Stacksync is built with security best practices to keep your data safe at every layer, and is DPF-certified for US, EU, UK and CH data transfers.

  • SOC 2 Type II
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  • CCPA
  • DPF US-EU-UK-CH

SSO & SCIM

Let your users access Stacksync from your centralized user management systems. Works with Okta, Azure, Google SSO and more.

Alerts

Immediately get alerted about record syncing issues over email, Slack, PagerDuty and WhatsApp. Resolve issues from a centralized dashboard with retry and revert options.

Secure connection options

Securely connects to your systems with:

Record-level recovery

Inspect sync errors and use retry and revert controls to resolve failed updates.

Read the recovery guide

Implementation

Technical reference

Review setup, record relationships, testing, and recovery for your implementation.

Authentication, permissions and API limits

Connection requirements and limits

Shopify
Integration interface
GraphQL Admin API (primary) and REST Admin API (legacy)
Authentication
OAuth via a custom Shopify app: admin creates an app in the Shopify Dev Dashboard, enables required API scopes, sets the Stacksync redirect URL, then supplies shop name + Client ID and Client Secret to Stacksync
Change detection
The saved Stacksync guide does not specify the change-detection mechanism. Confirm it for the selected objects.
Read access
Available for supported records
Write access
Available for supported records
Setup requirements
  • Have the Shopify administrator create the custom app described in the connection guide and configure its required scopes and redirect URL.
  • Supply the shop name, client ID, and client secret through the Stacksync authorization flow.
Limitations to check
  • The saved catalog lists six supported object types. Objects outside that list require confirmation. The connector documents two-way sync; confirm writable fields and operations for each selected object.
Technical documentation

Documentation reviewed 2026-09-15. Check the linked guides for current account and record requirements.

Shopify setup guide
Snowflake
Integration interface
SQL via JDBC/ODBC and native drivers, plus the Snowflake SQL REST API
Authentication
Dedicated Snowflake service user + role with RSA key-pair authentication (Stacksync-provided public key), created via a setup script requiring SECURITY_ADMIN and ACCOUNTADMIN roles
Change detection
The saved Stacksync guide does not specify the change-detection mechanism. Confirm it for the selected objects.
Read access
Available for supported records
Write access
Available for supported records
Setup requirements
  • Have an administrator run the documented setup script for a dedicated service user and role with RSA key-pair authentication.
  • Specify the correct warehouse, database, schema, and account identifier. Verify table grants for the service role.
  • Existing tables need a non-null primary key with a UUID_STRING() default, as specified in the connector guide.
Limitations to check
  • The saved support matrix excludes external tables and marks materialized and ordinary views as not yet supported.
  • Geography and geometry fields are excluded by the saved connector guide.
Technical documentation

Documentation reviewed 2026-09-15. Check the linked guides for current account and record requirements.

Snowflake setup guide

Prepare Shopify and Snowflake access

Set up both accounts before testing the mapping. Use test records where available, and identify the account administrator who can approve access and help resolve setup errors.

Shopify setup checklist
  • Have the Shopify administrator create the custom app described in the connection guide and configure its required scopes and redirect URL.
  • Supply the shop name, client ID, and client secret through the Stacksync authorization flow.

Setup guides: Authorize Shopify

Snowflake setup checklist
  • Have an administrator run the documented setup script for a dedicated service user and role with RSA key-pair authentication.
  • Specify the correct warehouse, database, schema, and account identifier. Verify table grants for the service role.
  • Existing tables need a non-null primary key with a UUID_STRING() default, as specified in the connector guide.

Setup guides: Authorize Snowflake

Prepare to go live

Record the fields each system can update, the first-load cutoff, both record IDs, the expected update delay, and who handles errors. Complete the tests before production before expanding to more records.

Use the Shopify and Snowflake planning worksheet to capture these decisions. Record the access owner in the worksheet and enter credentials only in the connection setup.

See Stacksync in action · Review current pricing

Record identity and field ownership

Keep each record tied to its source ID. Use the references below to choose field owners and preserve relationships between records.

Download the mapping worksheet · CSV, no email required

Reporting dataset

Orders / Proposed sales order table in Snowflake (choose its name)

Plan a sales order dataset while preserving its source meaning.

Object-specific availability and field permissions determine this mapping. Use the restrictions shown for each record type.

Shopify
Documented record · ✅ Supported
Snowflake
Your database schema
Record identity
Preserve both the order ID and stable line IDs. Allow one order to relate to several shipments or invoices.
Field ownership
Decide which system approves the order and which can cancel or amend it after fulfillment begins.

Fields to include

  • Source order ID
  • Customer reference
  • Line references and quantities
  • Order status
  • Currency
Record dependencies
Create or locate the customer and products first; resolve taxes, currency, and fulfillment references.
Validation
Test a multi-line order, a partial cancellation, and two partial shipments. Compare line totals as well as the header.
Recovery
Check for an existing destination order before retrying a timed-out create; reconcile line IDs to avoid duplicate fulfillment.

References: Shopify: Orders documentation

Reporting dataset

Products / Proposed product or catalog item table in Snowflake (choose its name)

Plan a product or catalog item dataset while preserving its source meaning.

Object-specific availability and field permissions determine this mapping. Use the restrictions shown for each record type.

Shopify
Documented record · ✅ Supported
Snowflake
Your database schema
Record identity
Distinguish the product ID, variant ID, SKU, and price-list entry; they are not interchangeable keys.
Field ownership
Assign ownership for catalog content, price, and stock separately.

Fields to include

  • Source product ID
  • SKU or variant reference
  • Description
  • Unit of measure
  • Price-list reference
Record dependencies
Resolve units, variants, categories, and applicable price lists before order lines.
Validation
Test two variants of one product, a changed SKU, and a price that applies to only one market or currency.
Recovery
Repair the variant or price-list reference before retrying affected order lines; preserve existing transaction prices.

References: Shopify: Products documentation

Reporting dataset

ProductVariants / Proposed product variant table in Snowflake (choose its name)

Plan a product variant dataset while preserving its source meaning.

Object-specific availability and field permissions determine this mapping. Use the restrictions shown for each record type.

Shopify
Documented record · ✅ Supported
Snowflake
Your database schema
Record identity
Retain variant ID separately from parent-product ID and SKU; a product with several variants must keep several identities.
Field ownership
Choose who owns variant definitions, prices, and availability; they may have different sources.

Fields to include

  • Source variant ID
  • Parent product reference
  • SKU
  • Option values
  • Unit or pricing reference
Record dependencies
Resolve the parent product and variant options before order or stock references.
Validation
Test two variants sharing a parent product and a changed SKU without losing order-line identity.
Recovery
Repair parent and variant references before retrying dependent inventory or order updates.

References: Shopify: ProductVariants documentation

Reporting dataset

Customers / Proposed customer table in Snowflake (choose its name)

Plan a customer dataset while preserving its source meaning.

Object-specific availability and field permissions determine this mapping. Use the restrictions shown for each record type.

Shopify
Documented record · ✅ Supported
Snowflake
Your database schema
Record identity
Determine whether each customer represents an individual, a company, or a business-unit relationship before matching it to a contact or organization. Retain the source customer ID and destination ID; names and email alone are insufficient.
Field ownership
Separate the customer relationship from contact details, billing authority, and consent. Choose an owner for each field after identifying whether the customer is a person or company.

Fields to include

  • Source customer ID
  • Person/company classification
  • Legal entity or business unit
  • Destination identity reference
Record dependencies
Resolve person or company type, legal entity, business role, and any billing account before transactions.
Validation
Test an individual buyer, a company buyer, and one company with multiple billing relationships. Do not merge these into a single generic contact.
Recovery
Hold ambiguous customer matches for review and resolve customer type before retrying dependent records.

References: Shopify: Customers documentation

Compare integration approaches

Use Shopify Orders and Snowflake Proposed sales order table in Snowflake (choose its name) for the first pilot. Verify its identity and permitted direction, then add dependent records only when the acceptance checks pass.

Stacksync managed sync

Best fit
Two-way sync for supported objects. Choose the records, writable fields, and permissions for your workflow.
Operating responsibility
Fits ongoing record synchronization when the required operations are supported. Add workflow steps for approvals or business actions that go beyond copying fields.
Before you choose
Check record matching: Preserve both the order ID and stable line IDs. Allow one order to relate to several shipments or invoices. Verify field coverage, deletion handling, and how changes are detected.

Native vendor integration

Best fit
A vendor-built integration may fit if it supports your Shopify and Snowflake record types.
Operating responsibility
Can reduce setup for a supported workflow. You may need another method for records or business steps it does not cover.
Before you choose
First check whether either vendor offers this integration. If available, verify Orders / Proposed sales order table in Snowflake (choose its name), update direction, account tier, and related-record handling.

Custom API or workflow

Best fit
Consider when Shopify and Snowflake need a transformation, approval, or action outside a direct record sync.
Operating responsibility
Provides control over business steps; the team owns credentials, version changes, error queues, and reconciliation.
Before you choose
Verify endpoint permissions, pagination, quotas, duplicate detection, and failure recovery.

File or scheduled snapshot

Best fit
Consider for a one-time Shopify / Snowflake migration or a reporting need with an explicit freshness window.
Operating responsibility
Can simplify a bounded transfer; later changes and deletion history require another extraction or a separately designed incremental process.
Before you choose
Record the extraction cutoff, source IDs, encoding, date/number formats, and reconciliation totals.

Workflow scenarios and expected results

Sales order reporting workflow

Object-specific availability and field permissions determine this mapping. Use the restrictions shown for each record type.

Starting event: A change to the selected Orders or Proposed sales order table in Snowflake (choose its name) record needs a defined result in the other system.

  1. Start with Shopify Orders and Snowflake Proposed sales order table in Snowflake (choose its name). Use the record-matching and field-ownership rules from your mapping worksheet.
  2. Create or locate the customer and products first; resolve taxes, currency, and fulfillment references.
  3. Test a normal update and one failed or repeated update in the supported direction. Keep both record IDs with the test results.

Expected result: Test a multi-line order, a partial cancellation, and two partial shipments. Compare line totals as well as the header.

If it fails: Check for an existing destination order before retrying a timed-out create; reconcile line IDs to avoid duplicate fulfillment.

Product or catalog item reporting workflow

Object-specific availability and field permissions determine this mapping. Use the restrictions shown for each record type.

Starting event: A change to the selected Products or Proposed product or catalog item table in Snowflake (choose its name) record needs a defined result in the other system.

  1. Start with Shopify Products and Snowflake Proposed product or catalog item table in Snowflake (choose its name). Use the record-matching and field-ownership rules from your mapping worksheet.
  2. Resolve units, variants, categories, and applicable price lists before order lines.
  3. Test a normal update and one failed or repeated update in the supported direction. Keep both record IDs with the test results.

Expected result: Test two variants of one product, a changed SKU, and a price that applies to only one market or currency.

If it fails: Repair the variant or price-list reference before retrying affected order lines; preserve existing transaction prices.

Product variant reporting workflow

Object-specific availability and field permissions determine this mapping. Use the restrictions shown for each record type.

Starting event: A change to the selected ProductVariants or Proposed product variant table in Snowflake (choose its name) record needs a defined result in the other system.

  1. Start with Shopify ProductVariants and Snowflake Proposed product variant table in Snowflake (choose its name). Use the record-matching and field-ownership rules from your mapping worksheet.
  2. Resolve the parent product and variant options before order or stock references.
  3. Test a normal update and one failed or repeated update in the supported direction. Keep both record IDs with the test results.

Expected result: Test two variants sharing a parent product and a changed SKU without losing order-line identity.

If it fails: Repair parent and variant references before retrying dependent inventory or order updates.

Coordinate Shopify commerce data with Snowflake

Validate the selected objects and operations even where connector-level direction is documented.

Starting event: A catalog, order, or fulfillment change in Shopify matters to a selected destination dataset.

  1. Choose the commerce entity from Products or ProductVariants; separate products, variants, orders, and fulfillments.
  2. Preserve order and line references through the Snowflake process. Define many-to-one or one-to-many relationships explicitly.
  3. Assign separate ownership for commercial approval, inventory, and fulfillment, including partial cancellations or returns.

Expected result: A split fulfillment and repeated request preserve line quantities without duplicate orders or shipments.

If it fails: Look up existing downstream records before retrying creation; reconcile current order and fulfillment states.

Initial load and acceptance testing

Keep both record IDs with the expected and actual result. Reconcile the same filters and time window in each system.

Orders / Proposed sales order table in Snowflake (choose its name)

Test case

Test a multi-line order, a partial cancellation, and two partial shipments. Compare line totals as well as the header.

Expected result

The expected sales order relationship is preserved with no duplicate action or unintended write.

Products / Proposed product or catalog item table in Snowflake (choose its name)

Test case

Test two variants of one product, a changed SKU, and a price that applies to only one market or currency.

Expected result

The expected product or catalog item relationship is preserved with no duplicate action or unintended write.

ProductVariants / Proposed product variant table in Snowflake (choose its name)

Test case

Test two variants sharing a parent product and a changed SKU without losing order-line identity.

Expected result

The expected product variant relationship is preserved with no duplicate action or unintended write.

Customers / Proposed customer table in Snowflake (choose its name)

Test case

Test an individual buyer, a company buyer, and one company with multiple billing relationships. Do not merge these into a single generic contact.

Expected result

The expected customer relationship is preserved with no duplicate action or unintended write.

Direction and permissions

Test case

Check that each connected account can read and write the chosen objects. Exercise both directions with a test record before enabling production changes.

Expected result

Only an approved, supported direction and permitted fields are written.

Freshness and reconciliation

Test case

Measure source and destination times for the selected records under normal load and a burst. Reconcile IDs and values using the same filters and cutoff.

Expected result

The process meets its agreed freshness target and reconciliation has no unexplained differences.

Failed updates, retries and recovery

Start with the failed record and the destination error, then inspect the source value, field requirements, and access.

Rejected or repeated sales order change

Investigate

Inspect Shopify Orders and Snowflake Proposed sales order table in Snowflake (choose its name), their IDs, and the destination error.

Next action

Check for an existing destination order before retrying a timed-out create; reconcile line IDs to avoid duplicate fulfillment.

Rejected or repeated product or catalog item change

Investigate

Inspect Shopify Products and Snowflake Proposed product or catalog item table in Snowflake (choose its name), their IDs, and the destination error.

Next action

Repair the variant or price-list reference before retrying affected order lines; preserve existing transaction prices.

Rejected or repeated product variant change

Investigate

Inspect Shopify ProductVariants and Snowflake Proposed product variant table in Snowflake (choose its name), their IDs, and the destination error.

Next action

Repair parent and variant references before retrying dependent inventory or order updates.

A record type or update is unavailable

Investigate

Check the Shopify and Snowflake connector guides, account permissions, and any operations marked On Request.

Next action

Ask the integration team to confirm a supported way to handle that record. Verify whether it needs connector configuration or a separate workflow step.

Source and destination disagree after a retry

Investigate

Compare current source values, destination validation, identity mappings, and any side effects already completed.

Next action

Stacksync issue retry reads the current source state. Decide the intended state before retrying or reverting; reconcile downstream effects separately.

Read the Stacksync issues dashboard guide for retry and revert behavior.

Change detection and update delivery

How updates move between Shopify and Snowflake

See how each system detects changes and which updates the other system can receive. Each direction has its own permissions and record requirements.

Shopify Snowflake Timing depends on the connected systems

Detect changesThe saved Stacksync guide does not specify the change-detection mechanism. Confirm it for the selected objects.

Apply updatesSelected writable fields update in Snowflake. Its permissions and validation rules still apply; rejected records can be inspected in the Issues dashboard.

Snowflake Shopify Timing depends on the connected systems

Detect changesThe saved Stacksync guide does not specify the change-detection mechanism. Confirm it for the selected objects.

Apply updatesSelected writable fields update in Shopify. Its permissions and validation rules still apply; rejected records can be inspected in the Issues dashboard.

Update timing and record limits
  • Measure initial-load and ongoing-change latency separately. Source detection, selected objects, account limits, and destination validation determine the observed delay.
FAQ

Shopify and Snowflake integration FAQ

Further reading

Guides and resources

Next step

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