Jobber to PlanetScale Integration
AI-first ETL from Jobber into PlanetScale. Governed entities, incremental sync, typed landing tables.
How Datrise loads Jobber into PlanetScale
Datrise syncs Jobber's jobs, clients, quotes, invoices, visits, and expenses into PlanetScale as a typed table per source entity. Flexible or custom fields land in JSON columns, and timestamps such as created, updated, and status changes are typed as DATETIME.
Sync is incremental: Datrise uses a watermark on updated-at, applied with INSERT … ON DUPLICATE KEY UPDATE, so re-runs update only what changed. Vitess sharding by tenant or entity key for very large tables. PlanetScale disallows foreign-key constraints by default, so Datrise models relationships by stable id columns rather than enforced FKs.
Ideal for horizontally scalable MySQL apps on Vitess.
Endpoints
Jobber: Field service quoting, scheduling, and job tracking.
PlanetScale: Serverless MySQL platform with safe schema workflows.
How Jobber entities map to PlanetScale
| Jobber entity | PlanetScale object | Notes |
|---|---|---|
| jobs | jobber_jobs | id PK · custom fields → JSON columns |
| clients | jobber_clients | id PK · linked to jobber_jobs |
| quotes | jobber_quotes | id PK · linked to jobber_jobs |
| invoices | jobber_invoices | id PK · linked to jobber_jobs |
FAQ
How does Datrise handle Jobber's custom fields in PlanetScale?
Flexible values are stored as JSON columns, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native PlanetScale types.
How does the Jobber to PlanetScale sync stay up to date?
It runs incrementally — Datrise uses a watermark on updated-at, applied with INSERT … ON DUPLICATE KEY UPDATE.
Related pipelines
More destinations for Jobber
More sources for PlanetScale
Early access
Connect Jobber to PlanetScale the easy way
Skip brittle scripts and manual exports. Join the waitlist to get a guided setup, AI-assisted mapping, and reliable incremental sync for this integration.