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Difference between Rank and Dense Rank in SQL

Difference between Rank and Dense Rank in SQL

Q: 1. What is the primary difference between RANK() and DENSE_RANK() in SQL?

The main distinction lies in how they handle ties: RANK() assigns the same rank to tied rows but skips subsequent ranks, leading to gaps. In contrast, DENSE_RANK() also assigns the same rank to ties but continues with the next consecutive rank, ensuring no gaps.

Q: 2. When should I use RANK() over DENSE_RANK()?

Use RANK() when it's important to reflect the presence of ties with gaps in ranking, such as in competitive scenarios where the position matters. DENSE_RANK() is preferable when you need a continuous ranking sequence without gaps, like in reporting or categorization tasks.

Q: 3. Do RANK() and DENSE_RANK() affect performance differently?

Generally, both functions have similar performance characteristics. However, performance can vary based on data size, indexing, and the complexity of the ORDER BY clause. It's advisable to analyze execution plans for optimization.

Q: 4. Can RANK() and DENSE_RANK() be used with PARTITION BY?

Yes, both functions can be combined with PARTITION BY to compute ranks within subsets of data, allowing for group-wise ranking based on specified columns.

Q: 5. How do RANK() and DENSE_RANK() handle NULL values?

In SQL, NULLs are treated as equal values. When ordering, NULLs are considered either highest or lowest based on the database's default behavior or specified ORDER BY clause. Both functions assign the same rank to NULLs accordingly.

Q: 6. What happens if I omit the ORDER BY clause in RANK() or DENSE_RANK()?

The ORDER BY clause is essential for defining the ranking criteria. Omitting it will result in a syntax error, as SQL requires a defined order to assign ranks.

Q: 7. Is there a difference in syntax between RANK() and DENSE_RANK()?

The syntax is similar for both functions:SELECT column1, RANK() OVER (PARTITION BY column2 ORDER BY column3) AS rank_columnFROM table_name;

Q: 8. Can I use RANK() and DENSE_RANK() in UPDATE or DELETE statements? While

not directly used in UPDATE or DELETE clauses, you can incorporate these functions within a Common Table Expression (CTE) or subquery to identify specific rows to update or delete based on their rank.

Q: 9 How do RANK() and DENSE_RANK() compare to ROW_NUMBER()?

ROW_NUMBER() assigns a unique sequential number to each row, regardless of duplicates. In contrast, RANK() and DENSE_RANK() assign the same rank to tied values, with RANK() introducing gaps and DENSE_RANK() maintaining consecutive ranks.

Q: 10. Are RANK() and DENSE_RANK() available in all SQL databases? Most modern

relational databases, including SQL Server, PostgreSQL, Oracle, and MySQL 8.0+, support these functions. However, syntax and behavior might vary slightly, so it's important to consult the specific database documentation.

By Mukesh Kumar

Updated on Apr 28, 2025 | 5 min read | 1.6k views

Table of Contents

Why does one query return a gap in ranking while another doesn’t—despite using almost identical SQL functions?
This confusion often arises when comparing RANK() and DENSE_RANK()—two powerful window functions used in SQL for assigning rankings within partitions.

RANK() assigns the same rank to tied values but skips the next rank(s), causing gaps. On the other hand, DENSE_RANK() also assigns the same rank to ties but continues with the next immediate rank—no gaps.

The key difference lies in how they handle ranking positions for duplicate values.

In this blog, we’ll demystify the differences between RANK and DENSE RANKusing real-world examples, practical SQL syntax, performance tips, and use cases to help you decide which one to use and when.

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What is RANK() in SQL?

RANK() is a window function in SQL used to assign a unique rank to rows within a result set based on the specified order of values. It is typically used with the OVER() clause and ORDER BY to generate rankings within partitions.

However, if two or more rows have the same value, RANK() assigns them the same rank—but skips the next rank(s), creating gaps.

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Syntax of Rank Function in SQL:

SELECT column1, column2,

RANK() OVER (PARTITION BY columnX ORDER BY columnY DESC) AS rank

FROM your_table;

Example:

Consider a sales table:

Employee	Revenue
Alice	1000
Bob	900
Charlie	900
Dave	800

Using RANK() on Revenue:

Employee	Revenue	Rank
Alice	1000	1
Bob	900	2
Charlie	900	2
Dave	800	4

Note: Rank 3 is skipped due to tie.

Use Cases:

Leaderboards with positional gaps (e.g., sports rankings)
Top-N reports with accurate positional ranking
Handling datasets with tied scores or values

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What is DENSE_RANK() in SQL?

DENSE_RANK() is a window function in SQL that assigns ranks to rows based on a specified order—but unlike RANK(), it does not skip ranks when duplicate values occur. This ensures consecutive ranking even when there are ties.

It’s especially useful when you want no gaps in the ranked output.

Syntax of Dense Rank in SQL:

SELECT column1, column2,

DENSE_RANK() OVER (PARTITION BY columnX ORDER BY columnY DESC) AS dense_rank

FROM your_table;

Example:

Using the same sales table:

Employee	Revenue
Alice	1000
Bob	900
Charlie	900
Dave	800

With DENSE_RANK() on Revenue:

Employee	Revenue	Dense_Rank
Alice	1000	1
Bob	900	2
Charlie	900	2
Dave	800	3

Note: No skipped ranks—ranks are dense and consecutive.

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Key Difference from RANK():

While both functions assign the same rank to tied values, DENSE_RANK() does not leave gaps in the sequence—unlike RANK().

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Rank vs Dense Rank: Key Differences Between Rank and Dense Rank

Parameter	RANK()	DENSE_RANK()
Ranking Logic	Assigns the same rank to ties, then skips the next rank(s)	Assigns the same rank to ties, no ranks are skipped
Gaps in Ranking	Yes – introduces gaps after duplicates	No – ranks remain consecutive even with ties
Use Case	Best for ranking where position matters (e.g., leaderboard)	Best for reports with strict rank order continuity
Output Behavior (with Ties)	Ties get same rank, next rank jumps ahead	Ties get same rank, next rank is just one higher
Syntax	RANK() OVER (PARTITION BY ... ORDER BY ...)	DENSE_RANK() OVER (PARTITION BY ... ORDER BY ...)
Performance	Nearly identical performance	Nearly identical performance
First Rank Assigned	Always starts from 1	Always starts from 1
Result Consistency	Varies when there are ties	More consistent in sequential ranking
Gap Sensitivity	Sensitive to duplicates – causes rank jumps	Ignores gaps caused by duplicates
Sorting Requirement	Requires ORDER BY in OVER() clause	Requires ORDER BY in OVER() clause
Standard Compliance	Part of SQL:2003 standard	Part of SQL:2003 standard
Ideal For	Competitive rankings, top-N with tie handling	Business reports, non-skip rank listings, product/category sorting

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SQL Query Examples: Rank vs Dense Rank in Action

Let’s take a simple dataset called sales_data:

Employee_ID	Employee_Name	Revenue
101	Alice	1000
102	Bob	900
103	Charlie	900
104	David	800
105	Eva	700

Using RANK():

SELECT Employee_Name, Revenue,

RANK() OVER (ORDER BY Revenue DESC) AS rank_position

FROM sales_data;

Output:

Employee_Name	Revenue	rank_position
Alice	1000	1
Bob	900	2
Charlie	900	2
David	800	4
Eva	700	5

Note: Rank 3 is skipped due to the tie between Bob and Charlie.

Using DENSE_RANK():

SELECT Employee_Name, Revenue,

DENSE_RANK() OVER (ORDER BY Revenue DESC) AS dense_rank_position

FROM sales_data;

Output:

Employee_Name	Revenue	dense_rank_position
Alice	1000	1
Bob	900	2
Charlie	900	2
David	800	3
Eva	700	4

Note: No ranks are skipped—ranking remains dense.

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RANK() and DENSE_RANK(): When to Use

Choosing between RANK() and DENSE_RANK() depends on how you want to handle ties in your result set and the business context of your report.

Use RANK() When:

Positional accuracy matters, including gaps in rankings.
You’re building competitive leaderboards (e.g., sports, sales contests).
You want to reflect real-world placement, where tied scores lead to skipped positions.
Example: In a marathon result table, if two runners tie for 2nd place, the next runner should be 4th—not 3rd.

Use DENSE_RANK() When:

You need consecutive ranking, even with tied values.
You’re generating category-wise reports or product rankings with no skipped positions.
Business needs demand a uniform ranking structure for downstream calculations or visualizations.
Example: In a product popularity chart, if two products share the same rank, the next should be just one step below.

In short, choose RANK() for accuracy with position gaps, and DENSE_RANK() for sequential clarity without gaps.

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Common Mistakes and How to Avoid Them

Even experienced developers can trip up when working with RANK() and DENSE_RANK(). Here are some frequent errors:

Mistake	Why It Happens	How to Fix It
Missing ORDER BY in OVER() clause	Without ORDER BY, ranking logic is undefined	Always specify ORDER BY inside the OVER() clause
Assuming ranks are unique	Ties result in duplicate ranks	Use ROW_NUMBER() if you need unique values
Not using PARTITION BY when needed	Ranks calculated over full dataset instead of group	Add PARTITION BY to segment results (e.g., by department)
Expecting continuous ranking from RANK()	RANK() introduces gaps	Use DENSE_RANK() for continuous ranking
Wrong column in ORDER BY	Leads to incorrect rank calculations	Double-check sorting logic based on requirement
Using RANK in WHERE clause directly	Window functions can't be used in WHERE	Use subqueries or CTEs to filter on ranks

Performance Considerations for Rank Functions

While RANK() and DENSE_RANK() are powerful, their performance can degrade with large datasets if not optimized properly.

Aspect	Insight	Optimization Tip
Execution Time	Both functions use sorting; expensive on large datasets	Create indexes on columns used in ORDER BY
Memory Usage	Sorting over wide partitions consumes memory	Minimize partition size when possible
Parallelism	Modern SQL engines parallelize window functions	Use efficient query plans and review EXPLAIN plans
Indexing	No direct index usage for window functions	But indexes on ORDER BY columns can improve sort performance
CTE/Subquery Overuse	Over-nesting leads to redundant computation	Materialize intermediate results or use temp tables for reuse
Filtering Ranked Rows	Filtering ranks requires another layer (CTE or subquery)	Use WITH clause and filter in outer query for clarity and speed

Conclusion: Which One Should You Use?

Both RANK() and DENSE_RANK() are powerful tools for ranking data, but the choice depends on the context of your analysis.

Choose RANK() when gaps in ranking matter—such as leaderboards, competitions, or use cases where positional accuracy reflects real-world hierarchy.
Opt for DENSE_RANK() when you need continuous, gap-free rankings—like reporting, product listings, or dashboards where visual clarity is key.

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