Snowplow to Supabase Integration
AI-first ETL from Snowplow into Supabase. Governed entities, incremental sync, typed landing tables.
How Datrise loads Snowplow into Supabase
Datrise syncs Snowplow's events, users, sessions, contexts, page views, and event schemas into Supabase as a typed table per source entity in your Supabase Postgres. Flexible or custom fields land in jsonb columns, and timestamps such as created, updated, and status changes are typed as timestamptz.
Sync is incremental: Datrise uses a watermark on updated-at, applied with INSERT … ON CONFLICT DO UPDATE, so re-runs update only what changed. Optional declarative partitioning for high-volume tables. Datrise lands into a dedicated schema and leaves row-level security to you, so synced tables don't inherit public access by accident.
Ideal for app builders who want CRM data alongside their Supabase product data.
Endpoints
Snowplow: Behavioral event pipeline with a strict schema.
Supabase: Postgres platform with auth, storage, and realtime APIs.
How Snowplow entities map to Supabase
| Snowplow entity | Supabase object | Notes |
|---|---|---|
| events | snowplow_events | timestamptz 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 Supabase?
Flexible values are stored as jsonb columns, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Supabase types.
How does the Snowplow to Supabase sync stay up to date?
It runs incrementally — Datrise uses a watermark on updated-at, applied with INSERT … ON CONFLICT DO UPDATE.
Related pipelines
More destinations for Snowplow
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