DatriseAI-first ETL

JSON File to PlanetScale Integration

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

How Datrise loads JSON File into PlanetScale

Datrise syncs JSON File's documents, nested objects, arrays, keys, file batches, and schemas 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

JSON File: Structured JSON documents from exports and drops.

PlanetScale: Serverless MySQL platform with safe schema workflows.

How JSON File entities map to PlanetScale

JSON File entityPlanetScale objectNotes
documentsjson_file_documentsid PK · custom fields → JSON columns
nested objectsjson_file_nested_objectsid PK · linked to json_file_documents
arraysjson_file_arraysid PK · linked to json_file_documents
keysjson_file_keysid PK · linked to json_file_documents

FAQ

How does Datrise handle JSON File'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 JSON File 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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