Merging Queries

[cingram11]

Is there a difference between merging queries and making a relationship in model view?

[collinq · Accepted solution]

Hi @cingram11 ,

At one level it is.  A merge combines two queries into one (Merge queries overview - Power Query | Microsoft Learn) and using the relationship does the same thing.  HOWEVER, the Merge functionality in Power Query allows you to select multiple fields upon which to use for the merge.  This is VERY different from the relationship in the model view.  The model view allows you to build the relationship on one field and one field only.  So, if you have only one field thenthe relationship works great.  BUT, if you have multiple fields, then the merge in Power Query is way more effective.

Then, you have to think about size of the queries and if you merge them what does that really mean?  You might want to create a key field of your own in each of the queries - and join on that field in the relationship in the data model and that would be a way to NOT have to use the merge.

[speedramps · Accepted solution]

This video may help

Learn about Merge and Relationships 

Also these learning paths

https://learn.microsoft.com/en-us/power-query/merge-queries-overview

https://learn.microsoft.com/en-us/power-bi/transform-model/desktop-create-and-manage-relationships

https://www.youtube.com/watch?v=vZndrBBPiQc

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[V-yubandi-msft]

Hi @cingram11 ,

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Thank You.

[V-yubandi-msft]

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[V-yubandi-msft]

Hi @cingram11 ,

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[V-yubandi-msft]

Hi @cingram11,

Thank you all for the valuable inputs shared above they effectively highlight the core differences between merging queries and creating relationships. I would like to add a few additional points that might assist others in evaluating which approach to use.

Use Case	Recommendation
Flattening data for simpler visuals	Merge Queries
Creating a reusable, scalable data model	Relationships (Model View)
Performance sensitive models	Prefer Relationships
Simple report with limited tables	Merge is OK

1. Merging is useful when you need a combined view of data upfront or need to join on multiple fields.

2. Relationships are ideal for large, dynamic, and scalable models, especially when using DAX. 

3. From a performance and maintenance perspective, relationships are often more efficient as they prevent data duplication and support better model structuring.

If there is any post helps, then please consider Accept it as the solution  to help the other members find it more quickly.

[danextian · Accepted solution]

Hi @cingram11 

Both merging and creating relationships in Power BI are akin to using VLOOKUP in Excel as they help bring related data together.

Merging in the Query Editor  allows you to combine data from two tables based on matching columns. Once merged, you can create new columns that pull in data from the related table, and you can immediately filter or transform the results within the query. The original table that you’re referencing doesn’t even need to be loaded into the data model as it can simply act as a helper query.

When you perform a merge, you can also control how the data is matched: for example, using an inner join will only keep rows that have matching values in both tables. A typical example: let’s say Query A contains product IDs, and Query B contains product IDs along with product names. If you merge these two queries and then filter for product names that contain a specific word, Power Query will only return the matching rows. However, this method can slow down performance, especially when dealing with large datasets or when have complex transformations happening before or after the merge. It adds extra load to the ETL process which can make refresh times longer.

On the other hand, creating relationships is done in the data model, after loading the tables. Unlike merging, relationships do not physically combine the tables. Each table stays separate, and the connection happens through a shared key column, like a product ID. This means you can build reports that dynamically pull related data without duplicating or reshaping the tables. Relationships are more efficient for large datasets because they let Power BI's engine handle the linking on the fly, instead of hard-processing the combinations during the query stage. For example, you can have a Sales table and a Products table connected by a product ID. You can then slice and filter sales data by product names from the related table without merging them.

Please refer to these - 
Merge queries overview 

Create and manage relationships in Power BI Desktop 

[speedramps · Accepted solution]

This video may help

Learn about Merge and Relationships 

Also these learning paths

https://learn.microsoft.com/en-us/power-query/merge-queries-overview

https://learn.microsoft.com/en-us/power-bi/transform-model/desktop-create-and-manage-relationships

https://www.youtube.com/watch?v=vZndrBBPiQc

Please click thumbs up because I have tried to help.

Then click accept solution if it answers your question.

You can accept multiple solutions from helpers, and it is polite to do so.

Thank you 

[collinq · Accepted solution]

Hi @cingram11 ,

At one level it is.  A merge combines two queries into one (Merge queries overview - Power Query | Microsoft Learn) and using the relationship does the same thing.  HOWEVER, the Merge functionality in Power Query allows you to select multiple fields upon which to use for the merge.  This is VERY different from the relationship in the model view.  The model view allows you to build the relationship on one field and one field only.  So, if you have only one field thenthe relationship works great.  BUT, if you have multiple fields, then the merge in Power Query is way more effective.

Then, you have to think about size of the queries and if you merge them what does that really mean?  You might want to create a key field of your own in each of the queries - and join on that field in the relationship in the data model and that would be a way to NOT have to use the merge.