DatriseAI-first ETL

Greenhouse to Supabase Integration

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

How Datrise loads Greenhouse into Supabase

Datrise syncs Greenhouse's candidates, applications, jobs, interviews, scorecards, and offers 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

Greenhouse: Applicant tracking and structured hiring.

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

How Greenhouse entities map to Supabase

Greenhouse entitySupabase objectNotes
candidatesgreenhouse_candidatesid PK · custom fields → jsonb columns
applicationsgreenhouse_applicationsid PK · linked to greenhouse_candidates
jobsgreenhouse_jobsid PK · linked to greenhouse_candidates
interviewsgreenhouse_interviewsid PK · linked to greenhouse_candidates

FAQ

How does Datrise handle Greenhouse'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 Greenhouse 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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