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Database ⇄ E-commerce

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

Keep AWS Aurora MySQL 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 MySQL and Bigcommerce

Give your engineers Bigcommerce's products, orders, and customers in AWS Aurora MySQL: 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 Orders, Customers, Categories, Brands from Bigcommerce into AWS Aurora MySQL 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 MySQL, 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 Sync a production Aurora cluster with an analytics database while filtering out sensitive columns.
  • 02 Let operations teams edit records in a spreadsheet-style tool with changes written back to Aurora safely.
  • 03 Write Inventory levels from a WMS or ERP onto BigCommerce Variants and SKUs so storefront availability reflects warehouse on-hand counts.
  • 04 Sync Customers and customer groups two-way with a CRM so marketing and support see the same accounts and addresses as the storefront.

Common sync patterns

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.

React to store changes

Updates in Bigcommerce arrive as row changes in AWS Aurora MySQL, so jobs and triggers can respond the moment an order, price, or stock level changes.

Keep catalog and inventory current

Prices, stock levels, or product details maintained in AWS Aurora MySQL sync back onto Bigcommerce, so the storefront shows what your systems treat as true.

What you can sync between AWS Aurora MySQL 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 MySQL objects Bigcommerce objects How this pairing syncs
Foreign keys Express relationships that syncs preserve when mapping to related objects elsewhere. 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. Foreign keys is specific to AWS Aurora MySQL and Products to Bigcommerce — each maps to any object or custom field on the other side.
Stored procedures and triggers Existing database logic keeps firing on rows written by a sync. 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. Stored procedures and triggers is specific to AWS Aurora MySQL and Variants and SKUs to Bigcommerce — each maps to any object or custom field on the other side.
Databases (schemas) Logical namespaces that scope which tables a sync connection can see. Orders V2 Orders API header, line items, and shipping/billing addresses; read into an ERP or accounting system, with status written back. Databases (schemas) is specific to AWS Aurora MySQL and Orders to Bigcommerce — each maps to any object or custom field on the other side.
Tables The primary sync unit; each table maps one-to-one to a table or object in the paired system. Customers V3 customer accounts, customer groups, and addresses; synced two-way with a CRM so storefront and GTM records match. Tables is specific to AWS Aurora MySQL and Customers to Bigcommerce — each maps to any object or custom field on the other side.
Rows Inserted, updated, and deleted individually or in bulk during two-way syncs. Categories Catalog V3 category tree; mapped for merchandising and kept aligned with a product master or PIM. Rows is specific to AWS Aurora MySQL and Categories to Bigcommerce — each maps to any object or custom field on the other side.
Columns MySQL data types are mapped to the paired system's field types during schema setup. Brands Catalog V3 brand records linked to products; kept aligned with a product master or PIM so brand names and pages stay consistent. Columns is specific to AWS Aurora MySQL and Brands to Bigcommerce — each maps to any object or custom field on the other side.

How changes propagate between AWS Aurora MySQL 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 MySQL Bigcommerce Sub-second propagation

DetectionChanges in AWS Aurora MySQL are captured at the source via change data capture — no polling loop against its API. Log-based CDC via the MySQL binary log (binlog), with polling on timestamp columns as a fallback.

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

Bigcommerce AWS Aurora MySQL 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 MySQL 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 MySQL ⇄ Bigcommerce

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

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

Real-time

Two-way sync

Changes in AWS Aurora MySQL 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 MySQL 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 MySQL or Bigcommerce record.

Observability

Monitoring

Track your AWS Aurora MySQL ⇄ 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 MySQL and Bigcommerce.

How the AWS Aurora MySQL and Bigcommerce connectors work

AWS Aurora MySQL

Integration surface
SQL wire protocol (MySQL-compatible), standard MySQL drivers and JDBC
Authentication
Database credentials, optionally AWS IAM database authentication, over TLS
Change detection
Log-based CDC via the MySQL binary log (binlog), with polling on timestamp columns 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 MySQL 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 MySQL 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 MySQL connected
    Bigcommerce connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

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

AWS Aurora MySQL 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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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 408 integrations available for AWS Aurora MySQL and Bigcommerce.

Popular · 7 of 408
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