DatriseAI-first ETL

MongoDB PlanetScale

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

How Datrise loads MongoDB into PlanetScale

Datrise syncs MongoDB's collections, documents, change streams, and schema snapshots 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

MongoDB: Document database often used as an operational source for analytics.

PlanetScale: Serverless MySQL platform with safe schema workflows.

How MongoDB entities map to PlanetScale

MongoDB entityPlanetScale objectNotes
collectionsmongodb_collectionsid PK · custom fields → JSON columns
documentsmongodb_documentsid PK · linked to mongodb_collections
change streamsmongodb_change_streamsDATETIME events
schema snapshotsmongodb_schema_snapshotsid PK · linked to mongodb_collections

FAQ

How does Datrise handle MongoDB'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 MongoDB 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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