Keap → Amazon Redshift
AI-first ETL from Keap into Amazon Redshift. Governed entities, incremental sync, typed landing tables.
How Datrise loads Keap into Amazon Redshift
Datrise syncs Keap's SMB contacts, opportunities, automations, and appointment workflows into Amazon Redshift as a typed table per source entity. Flexible or custom fields land in SUPER columns, and timestamps such as created, updated, and status changes are typed as TIMESTAMPTZ.
Sync is incremental: Datrise uses COPY from staged files, then a delete-and-insert merge on stable id, so re-runs update only what changed. A DISTKEY on the join id and a SORTKEY on the load timestamp. Redshift performance hinges on dist/sort keys, so Datrise picks them from your entity ids and sync timestamps rather than defaulting to EVEN distribution.
Ideal for AWS-native warehouses already using the Redshift ecosystem.
Endpoints
Keap: SMB CRM with pipeline automation, email, and appointment flows.
Amazon Redshift: AWS petabyte-scale warehouse with Spectrum.
How Keap entities map to Amazon Redshift
| Keap entity | Amazon Redshift object | Notes |
|---|---|---|
| SMB contacts | keap_smb_contacts | id PK · custom fields → SUPER columns |
| opportunities | keap_opportunities | id PK · linked to keap_smb_contacts |
| automations | keap_automations | id PK · linked to keap_smb_contacts |
| appointment workflows | keap_appointment_workflows | id PK · linked to keap_smb_contacts |
FAQ
How does Datrise handle Keap's custom fields in Amazon Redshift?
Flexible values are stored as SUPER columns, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Amazon Redshift types.
How does the Keap to Amazon Redshift sync stay up to date?
It runs incrementally — Datrise uses COPY from staged files, then a delete-and-insert merge on stable id.
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Early access
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