DatriseAI-first ETL

Parquet File PlanetScale

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

How Datrise loads Parquet File into PlanetScale

Datrise syncs Parquet File'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

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

PlanetScale: Serverless MySQL platform with safe schema workflows.

How Parquet File entities map to PlanetScale

Parquet File entityPlanetScale objectNotes
recordsparquet_file_recordsid PK · custom fields → JSON columns
eventsparquet_file_eventsDATETIME events
configuration objectsparquet_file_configuration_objectsid PK · linked to parquet_file_records

FAQ

How does Datrise handle Parquet 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 Parquet 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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