DatriseAI-first ETL

Housecall Pro to Google BigQuery Integration

AI-first ETL from Housecall Pro into Google BigQuery. Governed entities, incremental sync, typed landing tables.

How Datrise loads Housecall Pro into Google BigQuery

Datrise syncs Housecall Pro's jobs, customers, estimates, invoices, technicians, and service schedules into Google BigQuery as a partitioned table per source entity. Flexible or custom fields land in JSON or nested/repeated (STRUCT) columns, and timestamps such as created, updated, and status changes are typed as TIMESTAMP.

Sync is incremental: Datrise uses appends to a staging table, then MERGE on stable id into the partitioned target, so re-runs update only what changed. Partition by ingestion or event date and cluster by entity id to keep scanned bytes low. BigQuery bills by bytes scanned, so Datrise partitions and clusters every table to keep query costs predictable.

Ideal for Google-stack analytics and ML on serverless infrastructure.

Endpoints

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

Google BigQuery: Serverless analytics warehouse on GCP.

How Housecall Pro entities map to Google BigQuery

Housecall Pro entityGoogle BigQuery objectNotes
jobshousecall_pro_jobsid PK · custom fields → JSON or nested/repeated (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 Google BigQuery?

Flexible values are stored as JSON or nested/repeated (STRUCT) columns, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Google BigQuery types.

How does the Housecall Pro to Google BigQuery sync stay up to date?

It runs incrementally — Datrise uses appends to a staging table, then MERGE on stable id into the partitioned target.

Related pipelines

Early access

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