Odoo CRM → Oracle Database
AI-first ETL from Odoo CRM into Oracle Database. Governed entities, incremental sync, typed landing tables.
How Datrise loads Odoo CRM into Oracle Database
Datrise syncs Odoo CRM's modular CRM entities, opportunities, and revenue process data into Oracle Database as a typed table per source entity. Flexible or custom fields land in JSON or CLOB columns, and timestamps such as created, updated, and status changes are typed as TIMESTAMP WITH TIME ZONE.
Sync is incremental: Datrise uses a watermark on updated-at, applied with MERGE INTO, so re-runs update only what changed. Optional range partitioning by load date. Oracle treats an empty string as NULL, so Datrise distinguishes blank source values from missing ones during load.
Ideal for enterprise data teams consolidating CRM data into an Oracle warehouse.
Endpoints
Odoo CRM: Modular CRM in the Odoo suite for leads, opportunities, and revenue.
Oracle Database: Enterprise RDBMS with advanced partitioning and HA.
How Odoo CRM entities map to Oracle Database
| Odoo CRM entity | Oracle Database object | Notes |
|---|---|---|
| modular CRM entities | odoo_crm_modular_crm_entities | id PK · custom fields → JSON or CLOB 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 Oracle Database?
Flexible values are stored as JSON or CLOB columns, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Oracle Database types.
How does the Odoo CRM to Oracle Database sync stay up to date?
It runs incrementally — Datrise uses a watermark on updated-at, applied with MERGE INTO.
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Early access
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