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Database ⇄ CRM

AWS Aurora PostgreSQL to Shopify integration — real-time, two-way sync

Keep AWS Aurora PostgreSQL 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.

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

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Why teams connect AWS Aurora PostgreSQL and Shopify

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

Connecting Shopify to AWS Aurora PostgreSQL gives commerce and data teams an operational mirror of the store. Products, Orders, and Customers sync as Aurora tables and rows, so inventory logic, order reporting, and customer analysis run in SQL — with writes flowing back to the Shopify catalog.

Stacksync mirrors Orders, Customers, Abandoned Checkouts, Products from Shopify into Rows, Columns, Primary keys and constraints, Views and materialized views in AWS Aurora PostgreSQL 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

  • 01 Manage a large catalog by editing Products and ProductMedias through Aurora tables.
  • 02 Join Orders with application data in Postgres for lifetime-value analysis.
  • 03 Feed ERP and fulfillment systems from an Aurora mirror of live Shopify Orders.
  • 04 Mirror the product catalog from a PIM or database into Shopify products, variants, and metafields.

Common sync patterns

Order pipeline

Shopify Orders and Customers sync into Aurora tables for fulfillment systems and revenue reporting.

Catalog management from Postgres

ProductVariants updated as Aurora rows propagate back to Shopify Products.

Recovery targeting

Abandoned Checkouts land in an Aurora schema for cart-recovery analysis alongside customer data.

What you can sync between AWS Aurora PostgreSQL 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.

AWS Aurora PostgreSQL objects Shopify objects How this pairing syncs
Rows Inserted, updated, and deleted in both directions during bi-directional syncs. ProductMedias Synced with incremental and full sync per the Stacksync docs. Rows is specific to AWS Aurora PostgreSQL and ProductMedias to Shopify — each maps to any object or custom field on the other side.
Columns Rich Postgres types including JSONB and arrays are mapped to the paired system's fields. ProductVariants Synced with incremental and full sync per the Stacksync docs. Columns is specific to AWS Aurora PostgreSQL and ProductVariants to Shopify — each maps to any object or custom field on the other side.
Primary keys and constraints Identify rows for upserts and enforce integrity on sync writes. Orders Purchase transactions; pushed to ERPs for fulfillment and billing, and read into databases for reporting. Primary keys and constraints is specific to AWS Aurora PostgreSQL and Orders to Shopify — each maps to any object or custom field on the other side.
Views and materialized views Usable as read-only sources for filtered or precomputed sync datasets. Customers Buyer records; matched to CRM contacts for marketing and lifetime-value analysis. Views and materialized views is specific to AWS Aurora PostgreSQL and Customers to Shopify — each maps to any object or custom field on the other side.
Foreign keys Relationship metadata that syncs can translate into object references elsewhere. Abandoned Checkouts Synced with incremental and full sync per the Stacksync docs. Foreign keys is specific to AWS Aurora PostgreSQL and Abandoned Checkouts to Shopify — each maps to any object or custom field on the other side.
Replication slots and publications The logical replication objects that power log-based CDC. Products Catalog entries; often mastered in a PIM or ERP and written into Shopify. Replication slots and publications is specific to AWS Aurora PostgreSQL and Products to Shopify — each maps to any object or custom field on the other side.

How changes propagate between AWS Aurora PostgreSQL and Shopify

Each direction of the sync is driven by what the source system can signal and what the destination accepts — detection, delivery, and expected latency below.

AWS Aurora PostgreSQL Shopify Sub-second propagation

DetectionChanges in AWS Aurora PostgreSQL are captured at the source via change data capture — no polling loop against its API. Log-based CDC via PostgreSQL logical replication (WAL decoding through replication slots), with timestamp polling as a fallback.

DeliveryEach detected change is written to Shopify through its API, with automatic retries and rate-limit backoff.

Shopify AWS Aurora PostgreSQL Sub-second propagation

DetectionShopify notifies Stacksync of record changes through webhook events. Webhook topics per resource, with polling on updated_at as a fallback.

DeliveryEach detected change is applied to AWS Aurora PostgreSQL as a row-level write, with types converted between the two schemas.

Rate-limit considerations

  • Shopify: GraphQL uses a calculated query-cost budget; the REST API uses a leaky-bucket model.
What ships with AWS Aurora PostgreSQL ⇄ Shopify

Connect AWS Aurora PostgreSQL and Shopify for flexible, real-time data sync.

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever AWS Aurora PostgreSQL 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 AWS Aurora PostgreSQL or Shopify record.

Observability

Monitoring

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

Trading partners

EDI

Transform legacy EDI complexity into simple database interactions between AWS Aurora PostgreSQL and Shopify.

How the AWS Aurora PostgreSQL and Shopify connectors work

AWS Aurora PostgreSQL

Integration surface
SQL wire protocol (PostgreSQL-compatible), standard Postgres drivers and JDBC
Authentication
Database credentials, optionally AWS IAM database authentication, over TLS
Change detection
Log-based CDC via PostgreSQL logical replication (WAL decoding through replication slots), with timestamp polling as a fallback
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 AWS Aurora PostgreSQL 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 AWS Aurora PostgreSQL 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
    AWS Aurora PostgreSQL connected
    Shopify connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the AWS Aurora PostgreSQL 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 · AWS Aurora PostgreSQL ⇄ 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
    AWS Aurora PostgreSQL Shopify
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
Try interactive demo
FAQ

AWS Aurora PostgreSQL and Shopify integration FAQ

SECURITY

Security teams trust 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.

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→ 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 478 integrations available for AWS Aurora PostgreSQL and Shopify.

Popular · 7 of 478
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