DatriseAI-first ETL

Adobe Commerce (Magento) Sisense

AI-first ETL from Adobe Commerce (Magento) into Sisense. Governed entities, incremental sync, typed landing tables.

How Datrise loads Adobe Commerce (Magento) into Sisense

Datrise syncs Adobe Commerce (Magento)'s orders, products, customers, carts, and store views 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

Adobe Commerce (Magento): Enterprise e-commerce catalog, orders, and customer data.

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

How Adobe Commerce (Magento) entities map to Sisense

Adobe Commerce (Magento) entitySisense objectNotes
ordersmagento_ordersid PK · custom fields → flattened columns for the cube
productsmagento_productsid PK · linked to magento_orders
customersmagento_customersid PK · linked to magento_orders
cartsmagento_cartsid PK · linked to magento_orders

FAQ

How does Datrise handle Adobe Commerce (Magento)'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 Adobe Commerce (Magento) to Sisense sync stay up to date?

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

Related pipelines

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