Slack to Supabase Integration
AI-first ETL from Slack into Supabase. Governed entities, incremental sync, typed landing tables.
How Datrise loads Slack into Supabase
Datrise syncs Slack's channels, messages, users, threads, reactions, and channel memberships 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
Slack: Team messaging across channels and workspaces.
Supabase: Postgres platform with auth, storage, and realtime APIs.
How Slack entities map to Supabase
| Slack entity | Supabase object | Notes |
|---|---|---|
| channels | slack_channels | id PK · custom fields → jsonb columns |
| messages | slack_messages | id PK · linked to slack_channels |
| users | slack_users | id PK · linked to slack_channels |
| threads | slack_threads | id PK · linked to slack_channels |
FAQ
How does Datrise handle Slack'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 Slack 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 Slack
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