DatriseAI-first ETL

Adobe Commerce (Magento) DuckDB

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

How Datrise loads Adobe Commerce (Magento) into DuckDB

Datrise syncs Adobe Commerce (Magento)'s orders, products, customers, carts, and store views into DuckDB as a typed table per source entity in a DuckDB file. Flexible or custom fields land in JSON or STRUCT columns, and timestamps such as created, updated, and status changes are typed as TIMESTAMP WITH TIME ZONE.

Sync is incremental: Datrise uses rewrites changed entities into the local database (or Parquet) on each run, so re-runs update only what changed. Hive-partitioned Parquet by load date when exporting. DuckDB is single-writer and embedded, so Datrise produces a consistent file snapshot rather than concurrent streaming writes.

Ideal for local and notebook analytics without standing up a server.

Endpoints

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

DuckDB: In-process analytics database for fast local OLAP.

How Adobe Commerce (Magento) entities map to DuckDB

Adobe Commerce (Magento) entityDuckDB objectNotes
ordersmagento_ordersid PK · custom fields → JSON or STRUCT columns
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 DuckDB?

Flexible values are stored as JSON or STRUCT columns, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native DuckDB types.

How does the Adobe Commerce (Magento) to DuckDB sync stay up to date?

It runs incrementally — Datrise uses rewrites changed entities into the local database (or Parquet) on each run.

Related pipelines

Early access

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