HighLevel → Amazon Redshift
AI-first ETL from HighLevel into Amazon Redshift. Governed entities, incremental sync, typed landing tables.
How Datrise loads HighLevel into Amazon Redshift
Datrise syncs HighLevel's agency CRM records, funnels, opportunities, and messaging 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
HighLevel: Agency-focused CRM for leads, funnels, and customer messaging.
Amazon Redshift: AWS petabyte-scale warehouse with Spectrum.
How HighLevel entities map to Amazon Redshift
| HighLevel entity | Amazon Redshift object | Notes |
|---|---|---|
| agency CRM records | highlevel_agency_crm_records | id PK · custom fields → SUPER columns |
| funnels | highlevel_funnels | id PK · linked to highlevel_agency_crm_records |
| opportunities | highlevel_opportunities | id PK · linked to highlevel_agency_crm_records |
| messaging workflows | highlevel_messaging_workflows | id PK · linked to highlevel_agency_crm_records |
FAQ
How does Datrise handle HighLevel'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 HighLevel 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
Connect HighLevel to Amazon Redshift the easy way
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