DatriseAI-first ETL

Smaily PlanetScale

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

How Datrise loads Smaily into PlanetScale

Datrise syncs Smaily'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

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

PlanetScale: Serverless MySQL platform with safe schema workflows.

How Smaily entities map to PlanetScale

Smaily entityPlanetScale objectNotes
recordssmaily_recordsid PK · custom fields → JSON columns
eventssmaily_eventsDATETIME events
configuration objectssmaily_configuration_objectsid PK · linked to smaily_records

FAQ

How does Datrise handle Smaily'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 Smaily 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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