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Database ⇄ E-commerce

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

Keep AWS Aurora PostgreSQL and Bigcommerce 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 Bigcommerce

Give your engineers Bigcommerce's products, orders, and customers in AWS Aurora PostgreSQL: read them with normal queries, write inventory and prices back through the sync, and skip the storefront API.

E-commerce data sits behind an API built for the storefront, not for your internal systems. Teams that need those records, for order routing, inventory logic, reporting, or back-office tools, end up writing integration code against a rate-limited API and maintaining it through every catalog change and platform upgrade.

Stacksync mirrors Price Lists, Shipments, Products, Variants and SKUs from Bigcommerce into AWS Aurora PostgreSQL and keeps both sides consistent in real time. Whatever Bigcommerce holds, whether products, orders, customers, or inventory, those records become rows your code can query, and changes written in AWS Aurora PostgreSQL, such as new prices, stock levels, or fulfillment status, sync back into Bigcommerce with its validations respected.

Merchandising and operations keep working in the storefront, engineers keep working in the database, and neither side has to reconcile against a nightly export.

Common use cases

  • 01 Expose ERP records such as customers, orders, and invoices as Postgres tables the engineering team can query and update with plain SQL.
  • 02 Capture row-level changes with logical replication and propagate them to SaaS tools without batch jobs.
  • 03 Two-way sync of Products and Variants between BigCommerce and a PIM or ERP so catalog content, SKUs, and pricing stay aligned across systems.
  • 04 Write Inventory levels from a WMS or ERP onto BigCommerce Variants and SKUs so storefront availability reflects warehouse on-hand counts.

Common sync patterns

Controlled write-back

Choose exactly which tables and fields may flow from AWS Aurora PostgreSQL back into Bigcommerce, keeping the store authoritative on what it owns.

Read the store's data with a query

Records from Bigcommerce, whether products, orders, customers, or inventory, live in AWS Aurora PostgreSQL as ordinary tables or collections, joinable with the rest of your data.

Internal tools and automations without API code

Scripts and services read and write the synced tables; Stacksync handles the Bigcommerce API, rate limits, and retries.

What you can sync between AWS Aurora PostgreSQL and Bigcommerce

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 Bigcommerce objects How this pairing syncs
Columns Rich Postgres types including JSONB and arrays are mapped to the paired system's fields. Shipments Order shipments with tracking numbers; created in BigCommerce from a 3PL or fulfillment system as packages ship. Columns is specific to AWS Aurora PostgreSQL and Shipments to Bigcommerce — 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. Products Catalog V3 records with custom fields and images; mastered in a PIM or ERP and written to BigCommerce, or read out to a warehouse. Primary keys and constraints is specific to AWS Aurora PostgreSQL and Products to Bigcommerce — 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. Variants and SKUs Per-variant pricing and inventory; synced to keep stock and SKU data aligned with an ERP or WMS at the option level. Views and materialized views is specific to AWS Aurora PostgreSQL and Variants and SKUs to Bigcommerce — each maps to any object or custom field on the other side.
Foreign keys Relationship metadata that syncs can translate into object references elsewhere. Orders V2 Orders API header, line items, and shipping/billing addresses; read into an ERP or accounting system, with status written back. Foreign keys is specific to AWS Aurora PostgreSQL and Orders to Bigcommerce — 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. Customers V3 customer accounts, customer groups, and addresses; synced two-way with a CRM so storefront and GTM records match. Replication slots and publications is specific to AWS Aurora PostgreSQL and Customers to Bigcommerce — each maps to any object or custom field on the other side.
Databases and schemas PostgreSQL's two-level namespace scopes which tables a sync connection targets. Categories Catalog V3 category tree; mapped for merchandising and kept aligned with a product master or PIM. Databases and schemas is specific to AWS Aurora PostgreSQL and Categories to Bigcommerce — each maps to any object or custom field on the other side.

How changes propagate between AWS Aurora PostgreSQL and Bigcommerce

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 Bigcommerce 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 Bigcommerce through its API, with automatic retries and rate-limit backoff.

Bigcommerce AWS Aurora PostgreSQL Sub-second propagation

DetectionBigcommerce notifies Stacksync of record changes through webhook events. Webhooks push near-real-time events (store/order/*, store/product/*, store/customer/* and more).

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

Rate-limit considerations

  • Bigcommerce: OAuth quota refreshes every 30 seconds and varies by plan (about 20,000 requests/hour on Standard and Plus, 60,000 on Pro, higher on Enterprise); the X-Rate-Limit-Requests-Left header reports remaining calls.
What ships with AWS Aurora PostgreSQL ⇄ Bigcommerce

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

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

Real-time

Two-way sync

Changes in AWS Aurora PostgreSQL or Bigcommerce 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 Bigcommerce 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 Bigcommerce record.

Observability

Monitoring

Track your AWS Aurora PostgreSQL ⇄ Bigcommerce 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 Bigcommerce.

How the AWS Aurora PostgreSQL and Bigcommerce 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

Bigcommerce

Integration surface
REST Management API (V2 and V3), plus GraphQL Storefront and Admin APIs
Authentication
OAuth API account credentials — a store-generated client ID and permanent access token sent in the X-Auth-Token header, limited to the OAuth scopes granted when the account is created (e.g. store_v2_orders, store_v2_products)
Change detection
Webhooks push near-real-time events (store/order/*, store/product/*, store/customer/* and more); polling uses date_modified:min/max filters on Products, Orders, and Customers
Capabilities
read · write · webhooks
Rate limits
OAuth quota refreshes every 30 seconds and varies by plan (about 20,000 requests/hour on Standard and Plus, 60,000 on Pro, higher on Enterprise); the X-Rate-Limit-Requests-Left header reports remaining calls.
Bigcommerce setup guide
How it works

How to connect AWS Aurora PostgreSQL to Bigcommerce — 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 Bigcommerce 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
    Bigcommerce connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the AWS Aurora PostgreSQL and Bigcommerce 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 ⇄ Bigcommerce
    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 Bigcommerce
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
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FAQ

AWS Aurora PostgreSQL and Bigcommerce 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 410 integrations available for AWS Aurora PostgreSQL and Bigcommerce.

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