CSV File → Supabase
AI-first ETL from CSV File into Supabase. Governed entities, incremental sync, typed landing tables.
How Datrise loads CSV File into Supabase
Datrise syncs CSV File's records, events, and configuration objects 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
CSV File: SaaS or API data source for analytics and warehouse sync.
Supabase: Postgres platform with auth, storage, and realtime APIs.
How CSV File entities map to Supabase
| CSV File entity | Supabase object | Notes |
|---|---|---|
| records | csv_file_records | id PK · custom fields → jsonb columns |
| events | csv_file_events | timestamptz events |
| configuration objects | csv_file_configuration_objects | id PK · linked to csv_file_records |
FAQ
How does Datrise handle CSV File'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 CSV File to Supabase sync stay up to date?
It runs incrementally — Datrise uses a watermark on updated-at, applied with INSERT … ON CONFLICT DO UPDATE.
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