Real-time
Two-way sync
Changes in Bigcommerce or Postgres Heroku instantly reflect in both systems. No stale data, no manual imports.
E-commerce ⇄ Database
Bigcommerce to Postgres Heroku integration — real-time, two-way sync
Keep Bigcommerce and Postgres Heroku 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
Case study
Migrated from MuleSoft
Case study
Migrated from Celigo
Migrated from Heroku Connect
Migrated from Matillion
Case study
Migrated from Fivetran
Case study
Migrated from Celigo
Why teams connect Bigcommerce and Postgres Heroku
Give your engineers Bigcommerce's products, orders, and customers in Postgres Heroku: 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 Postgres Heroku 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 Postgres Heroku, 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 CRM objects as Postgres tables the Heroku application can query and join directly
- 02 Sync Heroku Postgres into a warehouse for reporting without running ETL dynos
- 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
Order data where your code can use it
Orders and their status become rows in Postgres Heroku for routing, fulfillment, and reporting, without polling the platform.
Controlled write-back
Choose exactly which tables and fields may flow from Postgres Heroku 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 Postgres Heroku as ordinary tables or collections, joinable with the rest of your data.
What you can sync between Bigcommerce and Postgres Heroku
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 | Postgres Heroku objects | How this pairing syncs | |
|---|---|---|---|
| Brands Catalog V3 brand records linked to products; kept aligned with a product master or PIM so brand names and pages stay consistent. | JSONB Columns Semi-structured payloads for nested SaaS objects and metadata. | Brands is specific to Bigcommerce and JSONB Columns to Postgres Heroku — 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. | Sequences Generate surrogate keys for rows created by inbound syncs. | Inventory is specific to Bigcommerce and Sequences to Postgres Heroku — 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. | Follower Databases Heroku-managed read replicas usable as low-impact sync sources. | Price Lists is specific to Bigcommerce and Follower Databases to Postgres Heroku — 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. | Tables Standard Postgres tables; the primary two-way sync target for app data. | Shipments is specific to Bigcommerce and Tables to Postgres Heroku — each maps to any object or custom field on the other side. | |
| 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. | Views Read-side projections exposed to outbound syncs. | Products is specific to Bigcommerce and Views to Postgres Heroku — each maps to any object or custom field on the other side. | |
| 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. | Materialized Views Precomputed result sets synced outward on refresh. | Variants and SKUs is specific to Bigcommerce and Materialized Views to Postgres Heroku — each maps to any object or custom field on the other side. |
How changes propagate between Bigcommerce and Postgres Heroku
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 Postgres Heroku 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 Postgres Heroku as a row-level write, with types converted between the two schemas.
Postgres Heroku Bigcommerce Interval-based propagation
DetectionStacksync polls Postgres Heroku for changes on an incremental schedule, reading only records changed since the previous pass. Trigger-based capture or polling in most configurations.
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.
- Postgres Heroku: No API rate limits; connection counts and performance are bounded by the Heroku Postgres plan.
What ships with Bigcommerce ⇄ Postgres Heroku
Connect Bigcommerce and Postgres Heroku for flexible, real-time data sync.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Bigcommerce–Postgres Heroku connection.
No-code + pro-code
Workflow automation
Trigger automated workflows whenever Bigcommerce or Postgres Heroku 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 Postgres Heroku record.
Observability
Monitoring
Track your Bigcommerce ⇄ Postgres Heroku 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 Postgres Heroku.
How the Bigcommerce and Postgres Heroku 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.
Postgres Heroku
- Integration surface
- SQL wire protocol (standard PostgreSQL)
- Authentication
- Database credentials from the Heroku DATABASE_URL config var; SSL required
- Change detection
- Trigger-based capture or polling in most configurations; log-based logical replication availability depends on plan and Heroku's managed server settings
- Capabilities
- read · write
- Rate limits
- No API rate limits; connection counts and performance are bounded by the Heroku Postgres plan
How it works
How to connect Bigcommerce to Postgres Heroku — 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.
- 01
Connect your apps
Authenticate Bigcommerce and Postgres Heroku with each platform's native method — OAuth, API keys, or service accounts — plus secure options like SSH tunneling, IP whitelisting, and VPC peering.
Bigcommerce
connected
Postgres Heroku
connected
OAuth 2.0SSH tunnelSSL certificateVPC peering - 02
Choose tables
Pick the Bigcommerce and Postgres Heroku 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.
objects · Bigcommerce ⇄ Postgres HerokuCustomers 12,480Sales Orders 8,213Invoices 5,902Items 1,344 - 03
Map fields
Fields map automatically even when names and types differ. Stacksync handles transformation and type casting for you, zero configuration required.
Bigcommerce Postgres HerokuCompany company_name textEmail email textAmount amount numericCreated created_at timestamp
FAQ
Bigcommerce and Postgres Heroku integration FAQ
-
Yes. Stacksync provides a managed, real-time two-way integration between Bigcommerce and Postgres Heroku: authenticate both systems, choose the objects to sync (such as Bigcommerce's Brands and Inventory), map fields visually, and changes propagate both ways in milliseconds — no code required.
-
On the Postgres Heroku side: Views, Materialized Views, Schemas, Primary and Unique Keys, plus custom fields where Postgres Heroku exposes them. On the Bigcommerce side: Orders, Customers, Categories, Brands. Stacksync auto-detects both schemas and converts types between the two systems.
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Yes. Each object mapping can be bidirectional or restricted to a single direction (both systems accept writes). Read-only mirrors, one-way pushes, and full two-way sync can be mixed in the same integration.
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Common patterns for Bigcommerce and Postgres Heroku: Order data where your code can use it; Controlled write-back; Read the store's data with a query. Orders and their status become rows in Postgres Heroku for routing, fulfillment, and reporting, without polling the platform.
-
Bigcommerce: 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). Postgres Heroku: SQL wire protocol (standard PostgreSQL). Authentication: Database credentials from the Heroku DATABASE_URL config var; SSL required. Stacksync manages authentication, retries, and rate limits on both sides.
-
Postgres Heroku: All connections require SSL, and server-level settings such as replication configuration are controlled by Heroku rather than the user. Bigcommerce: Inventory can be tracked at the product or variant level, and multi-location stock uses the separate V3 Inventory API, so writes must target the right model. Stacksync's field mapping accounts for these differences between Bigcommerce and Postgres Heroku without custom code.
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.
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:
Related integrations
Every pair below is a real-time, two-way sync. Search all 406 integrations available for Bigcommerce and Postgres Heroku.
Popular · 7 of 406
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Bigcommerce ⇄ Amazon Aurora -
Bigcommerce ⇄ Amazon Lightsail -
Bigcommerce ⇄ Apache Cassandra -
Bigcommerce ⇄ Azure Cosmos DB -
Postgres Heroku ⇄ Easypost -
Postgres Heroku ⇄ Magento -
Postgres Heroku ⇄ Shipwire
No integrations match .
