DatriseAI-first ETL

Microsoft Azure PlanetScale

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

How Datrise loads Microsoft Azure into PlanetScale

Datrise syncs Microsoft Azure'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

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

PlanetScale: Serverless MySQL platform with safe schema workflows.

How Microsoft Azure entities map to PlanetScale

Microsoft Azure entityPlanetScale objectNotes
recordsmicrosoft_azure_recordsid PK · custom fields → JSON columns
eventsmicrosoft_azure_eventsDATETIME events
configuration objectsmicrosoft_azure_configuration_objectsid PK · linked to microsoft_azure_records

FAQ

How does Datrise handle Microsoft Azure'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 Microsoft Azure 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

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