Move Odoo 17 data into Microsoft Fabric through secure, paginated REST exports built for large datasets — full and incremental loads with job monitoring.
The Microsoft Fabric Connector for Odoo 17 prepares selected Odoo model data for Microsoft Fabric. Administrators create export profiles, choose fields and filters, define full or incremental sync behaviour, and run exports manually or on schedule. Odoo builds compressed, paginated export files and exposes them through token-protected REST endpoints; Microsoft Fabric reads them with a standard REST source, follows the next-page URL, and loads the data into a Lakehouse or Warehouse — no direct database access, no custom scripts, no fragile one-off integrations.
Full & Incremental Exports
Rebuild Fabric tables from complete Odoo snapshots, or load only changed records using write_date watermark logic with id-based upserts in Fabric.
Built for Large Tables
Keyset pagination, compressed page files, progress checkpoints, and request throttling move large Odoo datasets page by page — validated with a 1.2 million row export benchmark.
Secure Token Access
Fabric reads token-protected REST endpoints — no direct PostgreSQL access, no database credentials leaving your Odoo infrastructure. Tokens are generated and revoked from Odoo.
Admin-Controlled Export Profiles
Choose exactly which Odoo models, fields, and filtered rows Fabric can read. Set sync mode, schedule, page size, and retention per profile from the Odoo UI.
Job Dashboard & Logs
Every export records status, row counts, page counts, duration, errors, and detailed logs — with retry actions and automatic cleanup of expired files.
Fabric REST Source Ready
Responses put rows under $.data with a next-page URL under $.next, so a Fabric Copy Job or Data Pipeline Copy Activity pages through the data with standard configuration.
Scheduling & Concurrency Control
Run exports manually or on daily/weekly schedules in off-hours windows, and cap simultaneous Fabric page requests to protect your Odoo server.
Lakehouse & Warehouse Destinations
Load full exports with overwrite or staging-and-merge, and incremental runs with upsert by id — into whichever Fabric destination your analytics team uses.
Odoo teams often rely on manual CSV exports, fragile scripts, or direct database access for analytics. The KSROlabs Microsoft Fabric Connector for Odoo 17 gives administrators a governed way to expose selected Odoo models to Fabric through token-protected REST endpoints.
Fabric pulls page-based responses from Odoo, reads records from $.data, follows $.next, and can upsert changed rows using write_date as the incremental watermark and id as the merge key.
A production workflow for exporting Odoo data into Microsoft Fabric without direct PostgreSQL access.
Configure connector
Install the Odoo 17 module, confirm the public Odoo URL, and generate a bearer token for Fabric.
Create export profiles
Define one profile per Odoo model with selected fields, filters, sync mode, schedule, and page size.
Odoo builds pages
Odoo queues the job, reads selected stored fields, writes compressed page files, and records progress.
Fabric follows next
Fabric uses a REST source, reads $.data, and follows AbsoluteUrl = $.next until all pages are loaded.
Monitor and retry
Admins review status, row counts, page counts, duration, errors, and logs from the Odoo job dashboard.
Configure Fabric Copy Job or Data Pipeline Copy Activity with row path $.data and pagination rule AbsoluteUrl = $.next. Odoo prepares the pages; Fabric follows the next URL until the export is complete.
{
"data": [{"id": 1, "name": "Example"}],
"has_more": true,
"next": "https://odoo.example.com/fabric/v2/jobs/<token>/pages/2"
}Common analytics and data warehouse scenarios for Odoo customers using Microsoft Fabric.
Finance analytics from Odoo accounting tables in Microsoft Fabric.
Sales and CRM reporting in Fabric Lakehouse, Warehouse, or Power BI.
Inventory, procurement, and operational dashboards from Odoo data.
Odoo data warehouse ingestion without direct PostgreSQL access.
Periodic Odoo reconciliation and controlled full refreshes in Fabric.
Large Odoo table exports with page-based loading and job visibility.
Key implementation details for Odoo administrators and Microsoft Fabric teams.
Odoo version
Odoo 17
Fabric connection
REST source in Copy Job or Data Pipeline Copy Activity
Authentication
Bearer token
Sync modes
Full export and incremental changed-row loading
Pagination
next URL in response body
Row path
$.data
Incremental watermark
write_date
Merge key
id
Large data strategy
Keyset pagination, compressed pages, checkpointed jobs
Scheduling
Manual, daily, and weekly
Monitoring
Job dashboard, errors, row counts, page counts, and logs
The connector was validated through direct REST/API testing, including authentication, pagination, incremental logic, error handling, logging, concurrency limits, and a 1.2 million row export benchmark.
Install the Microsoft Fabric Connector for Odoo 17 from the Odoo App Store — pricing available on the listing. Free setup support included with every purchase.
Common questions about the Microsoft Fabric Connector for Odoo 17.
It is an Odoo 17 module that turns Odoo into a controlled REST data source for Microsoft Fabric. Administrators create export profiles for the models they want to expose, select fields and filters, and choose full or incremental sync. Odoo builds compressed, paginated export files and serves them through token-protected REST endpoints; Fabric pulls the data with a standard REST source and loads it into a Lakehouse or Warehouse.
No. It is an Odoo module that exposes Fabric-compatible REST APIs. Microsoft Fabric connects to it using its standard REST source capabilities in a Copy Job or Data Pipeline Copy Activity.
No. Fabric reads token-protected REST endpoints exposed by Odoo. Database credentials remain inside the Odoo infrastructure, and administrators control exactly which models and fields are exposed through export profiles.
This connector is built for Odoo 17. Contact KSROlabs to discuss other Odoo versions — they would require separate migration and testing.
Yes. Odoo creates ready export jobs as compressed, paginated page files. Fabric starts from the job’s first page URL and follows the next field until all pages are loaded — ideal for first-time loads, dimension tables, and periodic reconciliation.
Yes. Fabric calls the live incremental endpoint with an updated_after watermark; Odoo returns rows whose write_date is newer, and Fabric upserts them by id. After a successful run, Fabric stores the returned max_write_date as the next watermark. This is scheduled or on-demand loading, not real-time streaming.
Not as delete events. Incremental export captures inserted and updated records. If delete reconciliation is required, use periodic full refreshes or a separate reconciliation process.
Yes — it is designed for large datasets using keyset pagination, selected stored fields, compressed NDJSON page files, progress checkpoints, retention cleanup, and request throttling. It was validated with a 1.2 million row export benchmark. Actual performance depends on table width, selected fields, indexes, disk speed, and Odoo server sizing.
Use a REST source in a Copy Job or Data Pipeline Copy Activity with row path $.data and pagination rule AbsoluteUrl = $.next, stopping when next is null or has_more is false. For full loads, overwrite the target or use staging plus merge; for incremental loads, upsert by id. No custom code is required, but the row path and pagination rule must be configured.
The Odoo job moves to Error status, stores the error details, and writes job logs. Failed jobs can be reviewed from the job dashboard and retried when appropriate. Queued and running jobs are protected against accidental deletion.
Yes. Each export profile selects the model, the stored fields to include, and optional domain filters, plus sync mode, schedule, and rows per page. The connector exports stored scalar fields — not every computed or relational field.
No. The connector exports Odoo data to Microsoft Fabric. It does not write Fabric data back into Odoo, and it is not a real-time transactional synchronisation tool.
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