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Hello,
How to understand when to use Copy job and when to set a pipeline with copy activity?
I feel confused and a bit overwhelmed with all the possibilities shared within Microsoft Fabric. I would like to understand the basic concept and the guidelines for using various functionalities in Fabric.
Is there a place where I can get all the information condensed about what to use in which case of data processing?
I would like to know:
1. the differences on performace, what better works for big sets of data and what can be used on small sets,
2. what can be used on hot and what on cold data
How to choose the right functionality to prepare a well-designed architecture that will assure the best performance?
Solved! Go to Solution.
Hi @syl-ade
Thank you for being part of the Microsoft Fabric Community.
Use Copy Job when you need to quickly move data from one place to another without much transformation. It's ideal for small or straightforward data loads and supports incremental loads efficiently.
Choose Pipeline with Copy Activity when your process is more complex and involves multiple steps, such as transformations, error handling, or triggering other activities. It allows for better orchestration and is suitable for automated and repeatable workflows.
For large datasets, pipelines with optimized copy activities (like partitioning and parallelism) provide better performance.
For small datasets, copy jobs work well since they are lightweight and quick to configure.
If your data is frequently accessed (hot data), pipelines help manage real-time or near-real-time processes more effectively.
If your data is seldom accessed (cold data), copy jobs are sufficient and more resource-efficient.
When designing your architecture, always consider data volume, frequency of access, complexity of the process, and required level of automation before choosing the right approach.
You can also refer to Microsoft’s official Fabric Decision Guide to get more detailed guidance.
If the above information helps you, please give us a Kudos and marked the Accept as a solution.
Best Regards,
Community Support Team _ C Srikanth.
Thank you!
Hi @syl-ade
Thank you for being part of the Microsoft Fabric Community.
Use Copy Job when you need to quickly move data from one place to another without much transformation. It's ideal for small or straightforward data loads and supports incremental loads efficiently.
Choose Pipeline with Copy Activity when your process is more complex and involves multiple steps, such as transformations, error handling, or triggering other activities. It allows for better orchestration and is suitable for automated and repeatable workflows.
For large datasets, pipelines with optimized copy activities (like partitioning and parallelism) provide better performance.
For small datasets, copy jobs work well since they are lightweight and quick to configure.
If your data is frequently accessed (hot data), pipelines help manage real-time or near-real-time processes more effectively.
If your data is seldom accessed (cold data), copy jobs are sufficient and more resource-efficient.
When designing your architecture, always consider data volume, frequency of access, complexity of the process, and required level of automation before choosing the right approach.
You can also refer to Microsoft’s official Fabric Decision Guide to get more detailed guidance.
If the above information helps you, please give us a Kudos and marked the Accept as a solution.
Best Regards,
Community Support Team _ C Srikanth.
Thank you!
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