DatriseAI-first ETL

Postmark App PlanetScale

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

How Datrise loads Postmark App into PlanetScale

Datrise syncs Postmark App's records, events, and configuration objects 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

Postmark App: SaaS or API data source for analytics and warehouse sync.

PlanetScale: Serverless MySQL platform with safe schema workflows.

How Postmark App entities map to PlanetScale

Postmark App entityPlanetScale objectNotes
recordspostmark_app_recordsid PK · custom fields → JSON columns
eventspostmark_app_eventsDATETIME events
configuration objectspostmark_app_configuration_objectsid PK · linked to postmark_app_records

FAQ

How does Datrise handle Postmark App'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 Postmark App 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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