Snowflake → PlanetScale
AI-first ETL from Snowflake into PlanetScale. Governed entities, incremental sync, typed landing tables.
How Datrise loads Snowflake into PlanetScale
Datrise syncs Snowflake'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
Snowflake: SaaS or API data source for analytics and warehouse sync.
PlanetScale: Serverless MySQL platform with safe schema workflows.
How Snowflake entities map to PlanetScale
| Snowflake entity | PlanetScale object | Notes |
|---|---|---|
| records | snowflake_records | id PK · custom fields → JSON columns |
| events | snowflake_events | DATETIME events |
| configuration objects | snowflake_configuration_objects | id PK · linked to snowflake_records |
FAQ
How does Datrise handle Snowflake'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 Snowflake 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
More destinations for Snowflake
More sources for PlanetScale
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