DatriseAI-first ETL

Adobe Commerce (Magento) ClickHouse

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

How Datrise loads Adobe Commerce (Magento) into ClickHouse

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

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

ClickHouse: Columnar OLAP engine for fast aggregations.

How Adobe Commerce (Magento) entities map to ClickHouse

Adobe Commerce (Magento) entityClickHouse objectNotes
ordersmagento_ordersid PK · custom fields → JSON or Map 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 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 Adobe Commerce (Magento) 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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