DatriseAI-first ETL

PipeRun to PlanetScale Integration

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

How Datrise loads PipeRun into PlanetScale

Datrise syncs PipeRun's deals, contacts, companies, pipeline stages, activities, and sales teams 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

PipeRun: Sales pipeline management for Brazilian revenue teams.

PlanetScale: Serverless MySQL platform with safe schema workflows.

How PipeRun entities map to PlanetScale

PipeRun entityPlanetScale objectNotes
dealspiperun_dealsid PK · custom fields → JSON columns
contactspiperun_contactsid PK · linked to piperun_deals
companiespiperun_companiesid PK · linked to piperun_deals
pipeline stagespiperun_pipeline_stagesid PK · linked to piperun_deals

FAQ

How does Datrise handle PipeRun'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 PipeRun to PlanetScale sync stay up to date?

It runs incrementally — Datrise uses a watermark on updated-at, applied with INSERT … ON DUPLICATE KEY UPDATE.

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