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E-commerce ⇄ Database

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

Keep Bigcommerce and PostgreSQL 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 Bigcommerce and PostgreSQL

Give your engineers Bigcommerce's products, orders, and customers in 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 Customers, Categories, Brands, Inventory from Bigcommerce into 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 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 Let an application write to its own database and have those rows appear as records in business systems in near real time
  • 02 Consolidate data from several microservice databases into one operational Postgres store
  • 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

Read the store's data with a query

Records from Bigcommerce, whether products, orders, customers, or inventory, live in 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.

React to store changes

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

What you can sync between Bigcommerce and PostgreSQL

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.

Bigcommerce objects PostgreSQL objects How this pairing syncs
Customers V3 customer accounts, customer groups, and addresses; synced two-way with a CRM so storefront and GTM records match. JSONB Columns Hold semi-structured payloads such as nested SaaS objects or metadata. Customers is specific to Bigcommerce and JSONB Columns to PostgreSQL — each maps to any object or custom field on the other side.
Categories Catalog V3 category tree; mapped for merchandising and kept aligned with a product master or PIM. Sequences Generate surrogate keys for rows created by inbound syncs. Categories is specific to Bigcommerce and Sequences to PostgreSQL — each maps to any object or custom field on the other side.
Brands Catalog V3 brand records linked to products; kept aligned with a product master or PIM so brand names and pages stay consistent. Custom Types and Enums Constrain synced values to a fixed set, mirroring picklist fields. Brands is specific to Bigcommerce and Custom Types and Enums to PostgreSQL — each maps to any object or custom field on the other side.
Inventory Product- or variant-level stock, plus multi-location counts via the V3 Inventory API; written from a WMS to reflect on-hand quantities. Tables The primary sync target; rows map one-to-one to records in connected SaaS systems. Inventory is specific to Bigcommerce and Tables to PostgreSQL — each maps to any object or custom field on the other side.
Price Lists V3 price lists and records driving customer-group and B2B pricing; pushed from an ERP so tiered prices stay current. Views Read-side projections used to expose joined or filtered data to a sync. Price Lists is specific to Bigcommerce and Views to PostgreSQL — each maps to any object or custom field on the other side.
Shipments Order shipments with tracking numbers; created in BigCommerce from a 3PL or fulfillment system as packages ship. Materialized Views Precomputed result sets synced outward on a refresh schedule. Shipments is specific to Bigcommerce and Materialized Views to PostgreSQL — each maps to any object or custom field on the other side.

How changes propagate between Bigcommerce and PostgreSQL

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.

Bigcommerce 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 PostgreSQL as a row-level write, with types converted between the two schemas.

PostgreSQL Bigcommerce Sub-second propagation

DetectionChanges in PostgreSQL are captured at the source via change data capture — no polling loop against its API. Logical replication (wal_level = logical) for change data capture via the "Postgres" connector.

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

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.
  • PostgreSQL: No API rate limits; throughput is bounded by connection limits, instance resources, and replication slot throughput.
What ships with Bigcommerce ⇄ PostgreSQL

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

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Bigcommerce or PostgreSQL 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 Bigcommerce or PostgreSQL record.

Observability

Monitoring

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

Trading partners

EDI

Transform legacy EDI complexity into simple database interactions between Bigcommerce and PostgreSQL.

How the Bigcommerce and PostgreSQL connectors work

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

PostgreSQL

Integration surface
SQL wire protocol (PostgreSQL frontend/backend protocol)
Authentication
Database credentials (connection string or parameters), with optional SSL root certificate upload and optional SSH tunnel (SSH user + host); a least-privilege DB user
Change detection
Logical replication (wal_level = logical) for change data capture via the "Postgres" connector; database triggers (TRIGGER grant + stacksync_logging schema) via the trigger-based "Postgres Heroku" connector where
Capabilities
read · write · CDC
Rate limits
No API rate limits; throughput is bounded by connection limits, instance resources, and replication slot throughput
PostgreSQL setup guide
How it works

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

    Choose tables

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

Bigcommerce and PostgreSQL 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.

Learn more about security
SOC 2 Type II
ISO 27001
HIPAA BAA
GDPR
CCPA
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 503 integrations available for Bigcommerce and PostgreSQL.

Popular · 8 of 503
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