DatriseAI-first ETL

Whisky Hunter PlanetScale

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

How Datrise loads Whisky Hunter into PlanetScale

Datrise syncs Whisky Hunter'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

Whisky Hunter: SaaS or API data source for analytics and warehouse sync.

PlanetScale: Serverless MySQL platform with safe schema workflows.

How Whisky Hunter entities map to PlanetScale

Whisky Hunter entityPlanetScale objectNotes
recordswhisky_hunter_recordsid PK · custom fields → JSON columns
eventswhisky_hunter_eventsDATETIME events
configuration objectswhisky_hunter_configuration_objectsid PK · linked to whisky_hunter_records

FAQ

How does Datrise handle Whisky Hunter'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 Whisky Hunter 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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