DatriseAI-first ETL

Keap PostgreSQL

AI-first ETL from Keap into PostgreSQL. Governed entities, incremental sync, typed landing tables.

How Datrise loads Keap into PostgreSQL

Datrise syncs Keap's SMB contacts, opportunities, automations, and appointment workflows 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

Keap: SMB CRM with pipeline automation, email, and appointment flows.

PostgreSQL: Open-source relational database with strong SQL and extensions.

How Keap entities map to PostgreSQL

Keap entityPostgreSQL objectNotes
SMB contactskeap_smb_contactsid PK · custom fields → jsonb columns
opportunitieskeap_opportunitiesid PK · linked to keap_smb_contacts
automationskeap_automationsid PK · linked to keap_smb_contacts
appointment workflowskeap_appointment_workflowsid PK · linked to keap_smb_contacts

FAQ

How does Datrise handle Keap'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 Keap 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.

Related pipelines

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