Forum Discussion
AlexanderPowBI
Resolver I
Resolver IPros and cons of using SQL in notebook to write data to warehouse vs. stored procedures
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
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. If this is helpful , please accept the answer and give kudos
2 Replies
- nilendraFabric
Super User
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. If this is helpful , please accept the answer and give kudos
- 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.
