DatriseAI-first ETL

Linnworks to Databricks SQL Warehouse Integration

AI-first ETL from Linnworks into Databricks SQL Warehouse. Governed entities, incremental sync, typed landing tables.

How Datrise loads Linnworks into Databricks SQL Warehouse

Datrise syncs Linnworks's orders, stock items, channels, shipments, suppliers, and inventory levels into Databricks SQL Warehouse as a Delta Lake table per source entity. Flexible or custom fields land in VARIANT or STRUCT columns, and timestamps such as created, updated, and status changes are typed as TIMESTAMP.

Sync is incremental: Datrise uses a Delta MERGE on stable id, with change history available via time travel, so re-runs update only what changed. Delta partitioning by load date with OPTIMIZE/Z-ORDER on query keys. Datrise writes Unity Catalog–governed Delta tables, so lineage and permissions are managed centrally rather than per-notebook.

Ideal for lakehouse analytics and ML feature tables on Databricks.

Endpoints

Linnworks: Multichannel order and inventory management.

Databricks SQL Warehouse: Lakehouse SQL endpoints over Delta tables.

How Linnworks entities map to Databricks SQL Warehouse

Linnworks entityDatabricks SQL Warehouse objectNotes
orderslinnworks_ordersid PK · custom fields → VARIANT or STRUCT columns
stock itemslinnworks_stock_itemsid PK · linked to linnworks_orders
channelslinnworks_channelsid PK · linked to linnworks_orders
shipmentslinnworks_shipmentsid PK · linked to linnworks_orders

FAQ

How does Datrise handle Linnworks's custom fields in Databricks SQL Warehouse?

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

How does the Linnworks to Databricks SQL Warehouse sync stay up to date?

It runs incrementally — Datrise uses a Delta MERGE on stable id, with change history available via time travel.

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