Pros and cons of using SQL in notebook to write data to warehouse vs. stored procedures

[AlexanderPowBI]

Hi,

When writing data from a lakehouse to a warehouse (and doing some transformations), I am wondering about theese two options:

1. Create stored procedure in warehouse and trigger it from my pipeline

2. Write the SQL in a notebook and trigger it from my pipeline

Is there any major drawbacks of using any of the two approaches? 

//Alexander

[ArwaAldoud]

Both options work, but the best choice depends on your needs.

I prefer using a notebook because it's more flexible you can mix SQL with Python/PySpark for advanced transformations. It's also easier to debug and test.

• Heavy transformations are usually done in the lakehouse (using PySpark/Spark SQL).
• Final transformations in the warehouse are often handled via stored procedures for efficiency.
• Notebooks are great for quick prototyping or handling complex logic.

[nilendraFabric · Accepted solution]

Hello @AlexanderPowBI 

• If your workload involves frequent experimentation or requires integration with tools like Spark or Power BI, notebooks might be a better fit.
• For standardized, high-performance ETL tasks that need to be reused across multiple pipelines or projects, stored procedures are more suitable.
• In Microsoft Fabric specifically, stored procedures often outperform notebooks for large-scale transformations due to their tight integration with the warehouse engine.

Feature	SQL in Notebooks	Stored Procedures
Interactivity	Highly interactive; great for exploration and debugging.	Less interactive; designed for predefined batch execution.
Performance	May incur overhead; not as optimized for large-scale operations.	Precompiled; optimized for high-performance transformations.
Flexibility	Supports integration with other languages (e.g., Python).	Limited to T-SQL; less flexible for multi-language workflows.
Maintainability	Can become fragmented in production setups.	Modular and reusable; easier to manage in production pipelines.
Security	Relies on workspace-level security; less granular control.	Strong RBAC and object-level security controls available.

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