Snowplow to PlanetScale Integration
AI-first ETL from Snowplow into PlanetScale. Governed entities, incremental sync, typed landing tables.
How Datrise loads Snowplow into PlanetScale
Datrise syncs Snowplow's events, users, sessions, contexts, page views, and event 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
Snowplow: Behavioral event pipeline with a strict schema.
PlanetScale: Serverless MySQL platform with safe schema workflows.
How Snowplow entities map to PlanetScale
| Snowplow entity | PlanetScale object | Notes |
|---|---|---|
| events | snowplow_events | DATETIME events |
| users | snowplow_users | id PK · linked to snowplow_events |
| sessions | snowplow_sessions | id PK · linked to snowplow_events |
| contexts | snowplow_contexts | id PK · linked to snowplow_events |
FAQ
How does Datrise handle Snowplow'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 Snowplow 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 Snowplow
More sources for PlanetScale
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