Two-way sync
Changes in Bigcommerce or SQL Server instantly reflect in both systems. No stale data, no manual imports.
Keep Bigcommerce and SQL Server in sync without custom scripts. Cut weeks of integration work, eliminate silent data drift, and give your team a single, reliable source of truth.
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 SQL Server 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 SQL Server, 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.
Records from Bigcommerce, whether products, orders, customers, or inventory, live in SQL Server as ordinary tables or collections, joinable with the rest of your data.
Scripts and services read and write the synced tables; Stacksync handles the Bigcommerce API, rate limits, and retries.
Updates in Bigcommerce arrive as row changes in SQL Server, so jobs and triggers can respond the moment an order, price, or stock level changes.
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 | SQL Server 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. | CDC Change Tables System-populated tables holding captured inserts, updates, and deletes for consumers. | Customers is specific to Bigcommerce and CDC Change Tables to SQL Server — 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. | Stored Procedures T-SQL logic that can validate or post-process synced rows. | Categories is specific to Bigcommerce and Stored Procedures to SQL Server — 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. | Databases Instance-level databases that scope a sync's reads and writes. | Brands is specific to Bigcommerce and Databases to SQL Server — 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. | Schemas Namespaces (dbo and custom) used to organize synced tables. | Inventory is specific to Bigcommerce and Schemas to SQL Server — 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. | Tables The primary sync target; rows map to records in connected systems. | Price Lists is specific to Bigcommerce and Tables to SQL Server — 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. | Views Read-side projections used as outbound sync sources. | Shipments is specific to Bigcommerce and Views to SQL Server — each maps to any object or custom field on the other side. |
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.
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 SQL Server as a row-level write, with types converted between the two schemas.
DetectionChanges in SQL Server are captured at the source via change data capture — no polling loop against its API. SQL Server Native Change Data Capture (CDC).
DeliveryEach detected change is written to Bigcommerce through its API, with automatic retries and rate-limit backoff.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Bigcommerce–SQL Server connection.
Changes in Bigcommerce or SQL Server instantly reflect in both systems. No stale data, no manual imports.
Trigger automated workflows whenever Bigcommerce or SQL Server data changes, update records, fire webhooks, or kick off sequences without brittle API scripts.
Handle millions of events per minute without losing a single Bigcommerce or SQL Server record.
Track your Bigcommerce ⇄ SQL Server sync health, view errors, and replay failed events in one click.
Transform legacy EDI complexity into simple database interactions between Bigcommerce and SQL Server.
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.
Authenticate Bigcommerce and SQL Server with each platform's native method — OAuth, API keys, or service accounts — plus secure options like SSH tunneling, IP whitelisting, and VPC peering.
Pick the Bigcommerce and SQL Server 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.
Fields map automatically even when names and types differ. Stacksync handles transformation and type casting for you, zero configuration required.
Yes. Stacksync provides a managed, real-time two-way integration between Bigcommerce and SQL Server: authenticate both systems, choose the objects to sync (such as Bigcommerce's Customers and Categories), map fields visually, and changes propagate both ways in milliseconds — no code required.
Common patterns for Bigcommerce and SQL Server: Read the store's data with a query; Internal tools and automations without API code; React to store changes. Records from Bigcommerce, whether products, orders, customers, or inventory, live in SQL Server as ordinary tables or collections, joinable with the rest of your data.
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). SQL Server: SQL over the TDS wire protocol (Tabular Data Stream), via ODBC/JDBC/ADO.NET drivers. Authentication: Database credentials entered as a connection string or as parameters (host/user/password) in the Create New Sync page. Stacksync manages authentication, retries, and rate limits on both sides.
SQL Server: Change Tracking is a lower-overhead alternative that records which rows changed, but not intermediate values, so it suits net-change syncs. 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 SQL Server without custom code.
Stacksync is SOC 2 Type II and ISO 27001 certified with HIPAA BAA support. Data is encrypted in transit, and a zero-persistent-storage architecture means Bigcommerce and SQL Server records are not retained after a sync operation.
Stacksync pricing is usage-based and starts at $1,000/month, including the managed Bigcommerce and SQL Server connectors, real-time two-way sync, monitoring, and support. That replaces building and maintaining a custom Bigcommerce–SQL Server integration in-house.
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.
Let your users access Stacksync from your centralized user management systems. Works with Okta, Azure, Google SSO and more.
Immediately get alerted about record syncing issues over email, Slack, PagerDuty and WhatsApp. Resolve issues from a centralized dashboard with retry and revert options.
Securely connects to your systems with:
Every pair below is a real-time, two-way sync. Search all 497 integrations available for Bigcommerce and SQL Server.