DatriseAI-first ETL

Odoo CRM Microsoft SQL Server

AI-first ETL from Odoo CRM into Microsoft SQL Server. Governed entities, incremental sync, typed landing tables.

How Datrise loads Odoo CRM into Microsoft SQL Server

Datrise syncs Odoo CRM's modular CRM entities, opportunities, and revenue process data into Microsoft SQL Server as a typed table per source entity. Flexible or custom fields land in NVARCHAR(MAX) JSON columns, and timestamps such as created, updated, and status changes are typed as datetime2.

Sync is incremental: Datrise uses a watermark on updated-at, applied with a MERGE statement, so re-runs update only what changed. Optional partitioned tables on a date partition function. SQL Server defaults to a case-insensitive collation, so Datrise preserves original casing in a metadata column to avoid silent key collisions.

Ideal for Microsoft-stack analytics and Power BI Import models.

Endpoints

Odoo CRM: Modular CRM in the Odoo suite for leads, opportunities, and revenue.

Microsoft SQL Server: Microsoft relational DB with enterprise features.

How Odoo CRM entities map to Microsoft SQL Server

Odoo CRM entityMicrosoft SQL Server objectNotes
modular CRM entitiesodoo_crm_modular_crm_entitiesid PK · custom fields → NVARCHAR(MAX) JSON columns
opportunitiesodoo_crm_opportunitiesid PK · linked to odoo_crm_modular_crm_entities
revenue process dataodoo_crm_revenue_process_dataid PK · linked to odoo_crm_modular_crm_entities

FAQ

How does Datrise handle Odoo CRM's custom fields in Microsoft SQL Server?

Flexible values are stored as NVARCHAR(MAX) JSON columns, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Microsoft SQL Server types.

How does the Odoo CRM to Microsoft SQL Server sync stay up to date?

It runs incrementally — Datrise uses a watermark on updated-at, applied with a MERGE statement.

Related pipelines

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