Odoo CRM → Amazon Redshift
AI-first ETL from Odoo CRM into Amazon Redshift. Governed entities, incremental sync, typed landing tables.
How Datrise loads Odoo CRM into Amazon Redshift
Datrise syncs Odoo CRM's modular CRM entities, opportunities, and revenue process data 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
Odoo CRM: Modular CRM in the Odoo suite for leads, opportunities, and revenue.
Amazon Redshift: AWS petabyte-scale warehouse with Spectrum.
How Odoo CRM entities map to Amazon Redshift
| Odoo CRM entity | Amazon Redshift object | Notes |
|---|---|---|
| modular CRM entities | odoo_crm_modular_crm_entities | id PK · custom fields → SUPER columns |
| opportunities | odoo_crm_opportunities | id PK · linked to odoo_crm_modular_crm_entities |
| revenue process data | odoo_crm_revenue_process_data | id PK · linked to odoo_crm_modular_crm_entities |
FAQ
How does Datrise handle Odoo CRM'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 Odoo CRM 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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