Migrating from Azure Machine Learning to Fabric

[pmscorca]

Hi,

in order to evaluate the migration of Azure Machine Learning workload to Fabric I think to use Fabric Data science as a proper destination workload.

Does it exist some feature comparisons between these two workloads, please?

Thanks

[Anonymous]

Hi @pmscorca 

May I ask if you have resolved this issue? If so, please mark the helpful reply and accept it as the solution. This will be helpful for other community members who have similar problems to solve it faster.

Thank you.

[Anonymous · Accepted solution]

Hi @pmscorca 
Thank you for reaching out microsoft fabric community forum.
While there's no official feature comparison yet between Azure Machine Learning and Fabric Data Science, here’s a  overview:

• Azure ML is a mature, full-featured platform ideal for advanced ML workloads, custom training, MLOps, and real-time inference. It’s best for data scientists and engineers working on complex or large-scale models.

• Fabric Data Science is newer and focuses on ease of use with strong integration into the Fabric ecosystem (OneLake, Power BI, Spark). It’s well-suited for simpler ML tasks, exploratory analysis, and business-user collaboration.

Use Fabric if you want a low-code, integrated environment for lighter workloads.
Stick with Azure ML for production-ready ML, deep customization, and advanced features.

If this solution helps, please consider giving us Kudos and accepting it as the solution so that it may assist other members in the community
Thank you.