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Sync BigCommerce Data to Flat Files & Spreadsheets

BigCommerce

Automatically sync your BigCommerce data to cloud storage and spreadsheets with Flatly's no-code, triggerless, turnkey integration service.

Historical & Dynamic Data
One-way Sync
For Non-technical Users

About the integration: Bigcommerce is a paid-for, hosted e-commerce solution that allows business owners to set up an online store and sell their products online. Flatly integrates with BigCommerce's official APIs.

Connect BigCommerce Which BigCommerce API does Flatly use?

Available Datasets

Flatly can sync the following datasets from BigCommerce.

  • Brands
  • Brands+Metafields Combo
  • Channels+Listings-All Combo
  • Coupons
  • Customers-Alltime
  • Customers-Last X days Date-ranged
  • Customers+Addresses-Alltime Combo
  • Customers+Addresses-Last X days Combo Date-ranged
  • Customers-All+Attributes Combo
  • CustomerGroups
  • CustomerAttributes
  • GiftCertificates
  • Orders-Alltime
  • Orders-Last X days Date-ranged
  • Orders+Messages-Alltime Combo
  • Orders+Messages-Last X days Combo Date-ranged
  • Orders+Products-Alltime Combo
  • Orders+Products-Last X days Combo Date-ranged
  • Orders+Shipments-Alltime Combo
  • Orders+Shipments-Last X days Combo Date-ranged
  • Orders+ShipAddresses-Alltime Combo
  • Orders+ShipAddresses-Last X days Combo Date-ranged
  • Orders+Taxes-Alltime Combo
  • Orders+Taxes-Last X days Combo Date-ranged
  • Orders+Transactions-Alltime Combo
  • Orders+Transactions-Last X days Combo Date-ranged
  • Products
  • Products+CustomFields Combo
  • Products+Metafields Combo
  • Products+Options Combo
  • Products+Reviews Combo
  • Products+Variants Combo
  • Pricelists
  • ShippingZones+Methods Combo
  • Sites+Routes-All Combo
  • Subscribers-Alltime
  • Subscribers-Last X days Date-ranged
  • Variants
  • Wishlists-AllCustomers

Send BigCommerce data to

Flatly can sync BigCommerce data to any of these destinations.

Note: Some destinations are aliased, for all intents and purposes they are functionally equivalent.

Querying BigCommerce - AI or ETL?

Many SaaS applications and databases can be directly queried within AI chat apps using connectors. For ad-hoc, single-user requests, this direct architecture is superior—it offers real-time visibility, high customizability, and bypasses the need for complex data pipelines.

However, ETL (Extract, Transform, Load) can be more favorable when certain requirements exist. You might consider transitioning to an ETL system and a centralized data store when:

  • Collaboration is required: Multiple stakeholders (colleagues, partners) need consistent access to the same shared single source of truth.
  • Downstream audiences: The queried data must be routed into other internal IT systems, published to team dashboards, or preserved in official records rather than remaining isolated in a chat window.
  • Data is complex: The raw data needs heavy cleaning or joining before an AI or non-technical user can accurately understand it.
  • Internal capabilities are limited: Your organization lacks the in-house programming resources or infrastructure necessary to reliably build, deploy, and maintain custom agentic workflows or complex data integrations from scratch.
  • Numerous accounts: When a high volume of identities or accounts within a data source need to be analyzed in bulk, a sophisticated connection manager is needed.
  • Concurrency & infrastructure: If many data sets need to be analyzed in parallel, concurrency can become an issue. The device hosting an AI agent can become saturated without concurrency controls in place, whereas an ETL pipeline is built to handle parallel workloads reliably.