DatriseAI-first ETL

Linnworks to ClickHouse Integration

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

How Datrise loads Linnworks into ClickHouse

Datrise syncs Linnworks's orders, stock items, channels, shipments, suppliers, and inventory levels into ClickHouse as a MergeTree table per source entity. Flexible or custom fields land in JSON or Map columns, and timestamps such as created, updated, and status changes are typed as DateTime64.

Sync is incremental: Datrise uses inserts into a ReplacingMergeTree keyed on stable id, so the latest version wins on merge, so re-runs update only what changed. Partition by month and order by (entity id, updated-at) for fast range scans. ClickHouse deduplicates asynchronously on merge, so Datrise uses ReplacingMergeTree and FINAL-safe queries rather than assuming immediate upserts.

Ideal for high-volume event analytics that need sub-second aggregation.

Endpoints

Linnworks: Multichannel order and inventory management.

ClickHouse: Columnar OLAP engine for fast aggregations.

How Linnworks entities map to ClickHouse

Linnworks entityClickHouse objectNotes
orderslinnworks_ordersid PK · custom fields → JSON or Map 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 ClickHouse?

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

How does the Linnworks to ClickHouse sync stay up to date?

It runs incrementally — Datrise uses inserts into a ReplacingMergeTree keyed on stable id, so the latest version wins on merge.

Related pipelines

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