Copper → PostgreSQL
AI-first ETL from Copper into PostgreSQL. Governed entities, incremental sync, typed landing tables.
How Datrise loads Copper into PostgreSQL
Datrise syncs Copper's Google Workspace CRM entities, opportunities, and relationship timelines into PostgreSQL as a typed table per source entity. 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 each entity's updated-at, applied with INSERT … ON CONFLICT DO UPDATE, so re-runs update only what changed. Optional declarative range partitioning by load date for high-volume tables. PostgreSQL folds unquoted identifiers to lowercase, so Datrise normalizes mixed-case source fields to snake_case.
Ideal for operational analytics and application backends that need fresh, queryable copies of your data.
Endpoints
Copper: Google Workspace-native CRM.
PostgreSQL: Open-source relational database with strong SQL and extensions.
How Copper entities map to PostgreSQL
| Copper entity | PostgreSQL object | Notes |
|---|---|---|
| Google Workspace CRM entities | copper_google_workspace_crm_entities | id PK · custom fields → jsonb columns |
| opportunities | copper_opportunities | id PK · linked to copper_google_workspace_crm_entities |
| relationship timelines | copper_relationship_timelines | timestamptz events |
FAQ
How does Datrise handle Copper's custom fields in PostgreSQL?
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 PostgreSQL types.
How does the Copper to PostgreSQL sync stay up to date?
It runs incrementally — Datrise uses a watermark on each entity's updated-at, applied with INSERT … ON CONFLICT DO UPDATE.
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Early access
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