DatriseAI-first ETL

Recharge Databricks SQL Warehouse

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

How Datrise loads Recharge into Databricks SQL Warehouse

Datrise syncs Recharge's subscriptions, charges, customers, plans, and churn events 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

Recharge: Subscription commerce for Shopify and recurring billing.

Databricks SQL Warehouse: Lakehouse SQL endpoints over Delta tables.

How Recharge entities map to Databricks SQL Warehouse

Recharge entityDatabricks SQL Warehouse objectNotes
subscriptionsrecharge_subscriptionsid PK · custom fields → VARIANT or STRUCT columns
chargesrecharge_chargesid PK · linked to recharge_subscriptions
customersrecharge_customersid PK · linked to recharge_subscriptions
plansrecharge_plansid PK · linked to recharge_subscriptions

FAQ

How does Datrise handle Recharge'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 Recharge 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.

Related pipelines

Early access

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