DatriseAI-first ETL

ServiceTitan to PlanetScale Integration

AI-first ETL from ServiceTitan into PlanetScale. Governed entities, incremental sync, typed landing tables.

How Datrise loads ServiceTitan into PlanetScale

Datrise syncs ServiceTitan's jobs, customers, estimates, invoices, technicians, and service agreements 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

ServiceTitan: Trades platform for dispatch, jobs, and revenue reporting.

PlanetScale: Serverless MySQL platform with safe schema workflows.

How ServiceTitan entities map to PlanetScale

ServiceTitan entityPlanetScale objectNotes
jobsservicetitan_jobsid PK · custom fields → JSON columns
customersservicetitan_customersid PK · linked to servicetitan_jobs
estimatesservicetitan_estimatesid PK · linked to servicetitan_jobs
invoicesservicetitan_invoicesid PK · linked to servicetitan_jobs

FAQ

How does Datrise handle ServiceTitan'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 ServiceTitan 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

Early access

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