Forum Discussion
Different behaviour between SQL database and SQL Analytics endpoint
- 4 months ago
Hi pmscorca ,
To align the SQL Analytics Endpoint with the SQL Database Editor, you need to explicitly call the Fabric REST API refreshMetadata operation. This forces the endpoint to sync its schema with the latest definitions.You don’t use this API inside the SQL Database Editor or SQL Analytics Endpoint UI directly it’s a REST API call that you trigger from your own automation or client code. In practice, you’d use it in one of these places:
1. Fabric Pipelines → Add a Web activity after your ingestion/transform steps to call the refreshMetadata API, so the SQL Analytics Endpoint is always aligned before downstream reporting.
2. Notebooks → Use Python (with requests or http libraries) to call the API as part of your workflow.
3. External scripts → PowerShell, Python, or any HTTP client can invoke the endpoint. This is common if you’re orchestrating refreshes outside Fabric.
4. CI/CD automation → Integrate the call into deployment pipelines so schema changes are automatically reflected in the SQL Analytics Endpoint.
For more details, you can refer to the official documentation:
Items - Refresh Sql Endpoint Metadata - REST API (SQLEndpoint) | Microsoft Learn
Thank you.
The SQL Analytics endpoint view should correspond to SQL database view.
Not really. The SQL Endpoint is a pared down, read only version. Cannot be used for transactions, only for consumption. Meta data synchronization is a one way street, and is not deterministic.
Hi, I don't understand the usefulness of the SQL analytics endpoint layer for a SQL database.
These two features don't align with each other, even over time.
- v-anbandari4 months agoCommunity Support
Hi pmscorca ,
It may seem that the SQL Database and SQL Analytics endpoint should behave the same, but they are designed for different purposes in Microsoft Fabric.
The SQL Database is used for transactional operations like insert, update, and delete. The SQL Analytics endpoint is a read-only layer used for reporting and analytical queries. The purpose is not to make both the same, but to allow analytics on the same data without affecting transactional performance and without moving data.
Because the SQL Analytics endpoint uses a different engine, some differences are expected, such as requiring datetime2 instead of datetime and slight delays in reflecting changes.
Both are meant to work together, not to behave exactly the same.
Thank you.