RANKX vs TOPN in Power BI: What’s the Difference and When to Use Each?

If you've ever tried to create a leaderboard in Power BI or highlight the top-performing products, chances are you’ve come across both RANKX and TOPN. And if you're like most people, you've probably wondered: “Aren’t they kind of doing the same thing?”

Short answer? Not quite.

Long answer? Well, that’s what this post is all about. Let’s unpack both functions, show where they shine, and most importantly—when to use which.

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What is RANKX?

RANKX is a DAX function used to assign a ranking to each item in a list, based on some value (like sales, profit, or customer satisfaction). It doesn’t filter your data—it adds context.

Syntax:

RANKX(
   table,
   expression,
   [value],
   [order],
   [ties]
)

Real-World Use Case:

You want to display the rank of each product based on total sales in your visuals—not just the top 5, but all of them, sorted and labeled by rank.

Example:

Product Rank = 
RANKX(
    ALL('Products'),
    [Total Sales],
    ,
    DESC
)

When to Use RANKX:

• You want to rank every row in your dataset.

• You want to display ranks alongside values in a table or matrix.

• You're dealing with dynamic filters (like slicers) and still want the rank to update accordingly.

• You need to compare relative positions, not just isolate the top performers.

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What is TOPN?

TOPN, on the other hand, is used to filter a table down to just the top N rows based on a numeric expression. It's more of a selector than a ranker.

Syntax:

TOPN(
    n_value,
    table,
    orderBy_expression,
    [order]
)

Real-World Use Case:

You want to create a visual that only shows the top 5 customers by revenue. You don’t care about the rest, and you're not looking to assign a rank to every customer.

Example:

Top 5 Customers = 
TOPN(
    5,
    ALL('Customers'),
    [Total Revenue],
    DESC
)

When to Use TOPN:

• You only want to see or analyze a specific number of top items (Top 3, Top 5, Top 10).

• You’re creating a card visual, bar chart, or table that should show only the best performers.

• You’re optimizing performance and don’t need to scan the full dataset.

• You want to feed a filtered table into another function (like SUMX, AVERAGEX, etc.).

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RANKX vs TOPN — Quick Comparison

Feature	RANKX	TOPN
Purpose	Assigns rank to every row	Filters to the top N rows
Output	Scalar value (rank)	Table
Use Case	Leaderboards, showing all ranks	Highlighting top performers
Dynamic Slicers	Adapts rank dynamically	Needs more setup for dynamic N
Can use in Measure?	Yes	Yes
Can use in Table Visual?	Yes	Yes, but filters the rows

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Bonus Tip: Combine Them Like a Pro

Here’s a trick: sometimes you want to rank your data and then show only the top N ranked items. That’s where you combine the two.

Top 5 by Rank =
CALCULATE (
    [Total Sales],
    FILTER (
        ADDCOLUMNS (
            ALL('Products'),
            "Rank", RANKX(ALL('Products'), [Total Sales])
        ),
        [Rank] <= 5
    )
)

This lets you filter by rank while keeping things dynamic—perfect when you're slicing and dicing your data all over the place.

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Final Thoughts

If Power BI were a kitchen, RANKX would be your label-maker—telling you where everything stands. TOPN would be your cherry-picker—grabbing only the cream of the crop.

They’re both powerful. They just serve different purposes.

Next time you're stuck between the two, ask yourself:

Do I want to label everything with a rank, or just filter the top results?

Once you answer that, the right DAX tool becomes obvious.

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Have any creative use cases with RANKX or TOPN? Drop them in the comments—I'd love to see how you're using them in your Power BI projects.