DatriseAI-first ETL

Housecall Pro to Databricks SQL Warehouse Integration

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

How Datrise loads Housecall Pro into Databricks SQL Warehouse

Datrise syncs Housecall Pro's jobs, customers, estimates, invoices, technicians, and service schedules 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

Housecall Pro: Home service scheduling, dispatch, and invoicing.

Databricks SQL Warehouse: Lakehouse SQL endpoints over Delta tables.

How Housecall Pro entities map to Databricks SQL Warehouse

Housecall Pro entityDatabricks SQL Warehouse objectNotes
jobshousecall_pro_jobsid PK · custom fields → VARIANT or STRUCT columns
customershousecall_pro_customersid PK · linked to housecall_pro_jobs
estimateshousecall_pro_estimatesid PK · linked to housecall_pro_jobs
invoiceshousecall_pro_invoicesid PK · linked to housecall_pro_jobs

FAQ

How does Datrise handle Housecall Pro'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 Housecall Pro 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

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