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Database ⇄ CRM

Neo4j to Shopify integration — real-time, two-way sync

Keep Neo4j and Shopify in sync without custom scripts. Cut weeks of integration work, eliminate silent data drift, and give your team a single, reliable source of truth.

  • SOC 2 and 6 other compliance frameworks
  • POC with real engineers in minutes

Adopted by fast-scaling companies moving mission-critical data in real time

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Why teams connect Neo4j and Shopify

Treat Shopify like part of your database: its records live in Neo4j as real tables, and writes in either place sync to the other in seconds.

Product and engineering teams constantly need CRM data, and the CRM API is a poor way to get it: rate limits, pagination, custom objects, and integration code that breaks when an admin renames a field. What they actually want is the data in Neo4j, where it can be queried and joined like everything else.

Stacksync mirrors Products, ProductMedias, ProductVariants, Orders from Shopify into Users & Roles, Nodes, Relationships, Properties in Neo4j with real-time, bi-directional sync. Read CRM records with plain queries; write updates from your application and they appear in Shopify with validation intact. Go-to-market teams keep working in the CRM, engineers keep working in the database, and neither has to think about the other.

Common use cases

  • Write inventory levels from a WMS or ERP into Shopify locations to keep availability accurate.
  • Mirror the product catalog from a PIM or database into Shopify products, variants, and metafields.
  • Sync product catalog and order history into Neo4j to power recommendation queries.
  • Feed identity and access data into a graph for entitlement and blast-radius analysis.

Trigger workflows from CRM changes

Field and stage updates in Shopify arrive as row changes in Neo4j, ready to drive jobs and notifications.

Query the CRM like a database

Accounts, contacts, and custom objects from Shopify become tables in Neo4j you can join with application data directly.

Product events onto CRM records

Signup, usage, or lifecycle changes written to Neo4j sync onto the matching records in Shopify, giving go-to-market teams live product context.

What you can sync between Neo4j and Shopify

Representative objects on each side — any object or custom field can map to any target. Schemas are auto-detected; types are converted between the two systems.

Neo4j objects Shopify objects
Relationships Typed, directed edges that carry the connections syncs exist to model. ProductVariants Synced with incremental and full sync per the Stacksync docs.
Properties Key-value attributes on both nodes and relationships, mapped from source fields. Orders Purchase transactions; pushed to ERPs for fulfillment and billing, and read into databases for reporting.
Labels Node type markers used to map source tables or objects onto the graph. Customers Buyer records; matched to CRM contacts for marketing and lifetime-value analysis.
Indexes & Constraints Uniqueness constraints and indexes that make MERGE-based upserts reliable and fast. Abandoned Checkouts Synced with incremental and full sync per the Stacksync docs.
Databases Named databases in a single instance that scope multi-tenant or multi-domain syncs. Products Catalog entries; often mastered in a PIM or ERP and written into Shopify.
Users & Roles Security principals controlling what an integration credential can query or modify. ProductMedias Synced with incremental and full sync per the Stacksync docs.
What ships with Neo4j ⇄ Shopify

Connect Neo4j and Shopify for flexible, real-time data sync.

Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Neo4j–Shopify connection.

Real-time

Two-way sync

Changes in Neo4j or Shopify instantly reflect in both systems. No stale data, no manual imports.

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Neo4j or Shopify data changes, update records, fire webhooks, or kick off sequences without brittle API scripts.

At scale

Event queues

Handle millions of events per minute without losing a single Neo4j or Shopify record.

Observability

Monitoring

Track your Neo4j ⇄ Shopify sync health, view errors, and replay failed events in one click.

Trading partners

EDI

Transform legacy EDI complexity into simple database interactions between Neo4j and Shopify.

How the Neo4j and Shopify connectors work

Neo4j

Integration surface
Bolt binary protocol with Cypher via official drivers, plus an HTTP query API
Authentication
Username/password (basic auth); enterprise deployments add SSO options
Change detection
Neo4j Change Data Capture on Enterprise and Aura streams graph changes; otherwise Cypher polling on timestamp properties
Capabilities
read · write · CDC

Shopify

Integration surface
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
Webhook topics per resource, with polling on updated_at as a fallback
Capabilities
read · write · webhooks
Rate limits
GraphQL uses a calculated query-cost budget; the REST API uses a leaky-bucket model.
Shopify setup guide
How it works

How to connect Neo4j to Shopify — three steps, no code

Configure and sync within minutes, no code. Whether you sync 50k or 100M+ records, Stacksync handles the queues, infra, and plumbing. Integrations are non-invasive and need zero setup on your systems.

  1. 01

    Connect your apps

    Authenticate Neo4j and Shopify with each platform's native method — OAuth, API keys, or service accounts — plus secure options like SSH tunneling, IP whitelisting, and VPC peering.

    • OAuth 2.0
    • SSH tunnel
    • VPC peering
    Neo4j connected
    Shopify connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the Neo4j and Shopify objects to sync — Stacksync auto-detects both schemas, including custom fields where the platform exposes them. Sync to existing tables, or let Stacksync create new ones with ideal data types.

    • Standard objects
    • Custom objects
    • Auto-schema
    objects · Neo4j ⇄ Shopify
    Customers 12,480
    Sales Orders 8,213
    Invoices 5,902
    Items 1,344
  3. 03

    Map fields

    Fields map automatically even when names and types differ. Stacksync handles transformation and type casting for you, zero configuration required.

    • Auto-map
    • Type casting
    • Transforms
    Neo4j Shopify
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
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FAQ

Neo4j and Shopify integration FAQ

SECURITY

Security teams love Stacksync

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.

Learn more about security
SOC 2 type II
ISO 27001
HIPAA BAA
GDPR
CCPA
CSA STAR
DPF US-EU-UK-CH
→ SECURITY WITH BENEFITS

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:

OAuth 2 SSH Tunnelling SSL certificates IP Whitelisting VPN gateway VPC peering and more

Related integrations

Every pair below is a real-time, two-way sync. Search all 386 integrations available for Neo4j and Shopify.

Popular · 8 of 386
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