DatriseAI-first ETL

BigCommerce to Sisense Integration

AI-first ETL from BigCommerce into Sisense. Governed entities, incremental sync, typed landing tables.

How Datrise loads BigCommerce into Sisense

Datrise syncs BigCommerce's orders, products, customers, carts, transactions, and categories into Sisense as modeled tables for a Sisense ElastiCube (or live connection). Flexible or custom fields land in flattened columns for the cube, and timestamps such as created, updated, and status changes are typed as date/time fields.

Sync is incremental: Datrise uses incremental ElastiCube builds on changed rows, so re-runs update only what changed. Date-partitioned facts to speed cube builds. ElastiCube is an in-memory model, so Datrise lands incremental, build-friendly tables rather than forcing full rebuilds.

Ideal for embedded analytics on an in-memory engine.

Endpoints

BigCommerce: Ecommerce platform for catalog, orders, and checkout.

Sisense: Analytics platform with elastic data models and embedded analytics.

How BigCommerce entities map to Sisense

BigCommerce entitySisense objectNotes
ordersbigcommerce_ordersid PK · custom fields → flattened columns for the cube
productsbigcommerce_productsid PK · linked to bigcommerce_orders
customersbigcommerce_customersid PK · linked to bigcommerce_orders
cartsbigcommerce_cartsid PK · linked to bigcommerce_orders

FAQ

How does Datrise handle BigCommerce's custom fields in Sisense?

Flexible values are stored as flattened columns for the cube, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Sisense types.

How does the BigCommerce to Sisense sync stay up to date?

It runs incrementally — Datrise uses incremental ElastiCube builds on changed rows.

Related pipelines

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