CSV File to PlanetScale Integration

How Datrise loads CSV File into PlanetScale

Datrise syncs CSV File's rows, columns, headers, delimiters, file batches, and encodings 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

CSV File: Delimited flat files from exports and drops.

PlanetScale: Serverless MySQL platform with safe schema workflows.

How CSV File entities map to PlanetScale

CSV File entity	PlanetScale object	Notes
rows	`csv_file_rows`	id PK · custom fields → JSON columns
columns	`csv_file_columns`	id PK · linked to csv_file_rows
headers	`csv_file_headers`	id PK · linked to csv_file_rows
delimiters	`csv_file_delimiters`	id PK · linked to csv_file_rows

FAQ

How does Datrise handle CSV 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 CSV 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

Early access

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