Odoo CRM → Databricks SQL Warehouse
AI-first ETL from Odoo CRM into Databricks SQL Warehouse. Governed entities, incremental sync, typed landing tables.
How Datrise loads Odoo CRM into Databricks SQL Warehouse
Datrise syncs Odoo CRM's modular CRM entities, opportunities, and revenue process data into Databricks SQL Warehouse as a Delta Lake table per source entity. Flexible or custom fields land in VARIANT or STRUCT columns, and timestamps such as created, updated, and status changes are typed as TIMESTAMP.
Sync is incremental: Datrise uses a Delta MERGE on stable id, with change history available via time travel, so re-runs update only what changed. Delta partitioning by load date with OPTIMIZE/Z-ORDER on query keys. Datrise writes Unity Catalog–governed Delta tables, so lineage and permissions are managed centrally rather than per-notebook.
Ideal for lakehouse analytics and ML feature tables on Databricks.
Endpoints
Odoo CRM: Modular CRM in the Odoo suite for leads, opportunities, and revenue.
Databricks SQL Warehouse: Lakehouse SQL endpoints over Delta tables.
How Odoo CRM entities map to Databricks SQL Warehouse
| Odoo CRM entity | Databricks SQL Warehouse object | Notes |
|---|---|---|
| modular CRM entities | odoo_crm_modular_crm_entities | id PK · custom fields → VARIANT or STRUCT 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 Databricks SQL Warehouse?
Flexible values are stored as VARIANT or STRUCT columns, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Databricks SQL Warehouse types.
How does the Odoo CRM to Databricks SQL Warehouse sync stay up to date?
It runs incrementally — Datrise uses a Delta MERGE on stable id, with change history available via time travel.
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Early access
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