DatriseAI-first ETL

Google Analytics Supabase

AI-first ETL from Google Analytics into Supabase. Governed entities, incremental sync, typed landing tables.

How Datrise loads Google Analytics into Supabase

Datrise syncs Google Analytics's sessions, events, channels, conversions, and behavior cohorts 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

Google Analytics: Web and product analytics for behavior and traffic insights.

Supabase: Postgres platform with auth, storage, and realtime APIs.

How Google Analytics entities map to Supabase

Google Analytics entitySupabase objectNotes
sessionsgoogle_analytics_sessionsid PK · custom fields → jsonb columns
eventsgoogle_analytics_eventstimestamptz events
channelsgoogle_analytics_channelsid PK · linked to google_analytics_sessions
conversionsgoogle_analytics_conversionsid PK · linked to google_analytics_sessions

FAQ

How does Datrise handle Google Analytics'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 Google Analytics 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

Early access

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