DatriseAI-first ETL

Microsoft Dataverse to PlanetScale Integration

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

How Datrise loads Microsoft Dataverse into PlanetScale

Datrise syncs Microsoft Dataverse's tables, rows, columns, relationships, choice sets, and change tracking 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 Dataverse: Business data platform behind Dynamics and Power Apps.

PlanetScale: Serverless MySQL platform with safe schema workflows.

How Microsoft Dataverse entities map to PlanetScale

Microsoft Dataverse entityPlanetScale objectNotes
tablesmicrosoft_dataverse_tablesid PK · custom fields → JSON columns
rowsmicrosoft_dataverse_rowsid PK · linked to microsoft_dataverse_tables
columnsmicrosoft_dataverse_columnsid PK · linked to microsoft_dataverse_tables
relationshipsmicrosoft_dataverse_relationshipsid PK · linked to microsoft_dataverse_tables

FAQ

How does Datrise handle Microsoft Dataverse'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 Dataverse 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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