Applies to: SQL Server Azure SQL Database Azure SQL Managed Instance Azure Synapse Analytics Analytics Platform System (PDW)

You can use the PIVOT and UNPIVOT relational operators to change a table-valued expression into another table. PIVOT rotates a table-valued expression by turning the unique values from one column in the expression into multiple columns in the output. And PIVOT runs aggregations where they're required on any remaining column values that are wanted in the final output. UNPIVOT carries out the opposite operation to PIVOT by rotating columns of a table-valued expression into column values.

The syntax for PIVOT is simpler and more readable than the syntax that may otherwise be specified in a complex series of SELECT...CASE statements. For a complete description of the syntax for PIVOT, see FROM (Transact-SQL).


The following syntax summarizes how to use the PIVOT operator.

SELECT <non-pivoted column>,  
    [first pivoted column] AS <column name>,  
    [second pivoted column] AS <column name>,  
    [last pivoted column] AS <column name>  
    (<SELECT query that produces the data>)   
    AS <alias for the source query>  
    <aggregation function>(<column being aggregated>)  
[<column that contains the values that will become column headers>]   
    IN ( [first pivoted column], [second pivoted column],  
    ... [last pivoted column])  
) AS <alias for the pivot table>  
<optional ORDER BY clause>;  


The column identifiers in the UNPIVOT clause follow the catalog collation. For SQL Database, the collation is always SQL_Latin1_General_CP1_CI_AS. For SQL Server partially contained databases, the collation is always Latin1_General_100_CI_AS_KS_WS_SC. If the column is combined with other columns, then a collate clause (COLLATE DATABASE_DEFAULT) is required to avoid conflicts.

In Microsoft Fabric and Azure Synapse Analytics pools, queries with PIVOT operator fail if there's a GROUP BY on the nonpivot column output by PIVOT. As a workaround, remove the nonpivot column from the GROUP BY. Query results are the same, as this GROUP BY clause is duplicate.

Basic PIVOT example

The following code example produces a two-column table that has four rows.

USE AdventureWorks2022;  
SELECT DaysToManufacture, AVG(StandardCost) AS AverageCost   
FROM Production.Product  
GROUP BY DaysToManufacture;  

Here is the result set.

DaysToManufacture AverageCost
----------------- -----------
0                 5.0885
1                 223.88
2                 359.1082
4                 949.4105

No products are defined with three DaysToManufacture.

The following code displays the same result, pivoted so that the DaysToManufacture values become the column headings. A column is provided for three [3] days, even though the results are NULL.

-- Pivot table with one row and five columns  
SELECT 'AverageCost' AS Cost_Sorted_By_Production_Days,   
  [0], [1], [2], [3], [4]  
  SELECT DaysToManufacture, StandardCost   
  FROM Production.Product
) AS SourceTable  
  FOR DaysToManufacture IN ([0], [1], [2], [3], [4])  
) AS PivotTable;  

Here is the result set.

Cost_Sorted_By_Production_Days 0           1           2           3           4         
------------------------------ ----------- ----------- ----------- ----------- -----------
AverageCost                    5.0885      223.88      359.1082    NULL        949.4105

Complex PIVOT example

A common scenario where PIVOT can be useful is when you want to generate cross-tabulation reports to give a summary of the data. For example, suppose you want to query the PurchaseOrderHeader table in the AdventureWorks2022 sample database to determine the number of purchase orders placed by certain employees. The following query provides this report, ordered by vendor.

USE AdventureWorks2022;  
SELECT VendorID, [250] AS Emp1, [251] AS Emp2, [256] AS Emp3, [257] AS Emp4, [260] AS Emp5  
(SELECT PurchaseOrderID, EmployeeID, VendorID  
FROM Purchasing.PurchaseOrderHeader) p  
COUNT (PurchaseOrderID)  
FOR EmployeeID IN  
( [250], [251], [256], [257], [260] )  
) AS pvt  
ORDER BY pvt.VendorID;  

Here's a partial result set.

VendorID    Emp1        Emp2        Emp3        Emp4        Emp5  
----------- ----------- ----------- ----------- ----------- -----------
1492        2           5           4           4           4
1494        2           5           4           5           4
1496        2           4           4           5           5
1498        2           5           4           4           4
1500        3           4           4           5           4

The results returned by this subselect statement are pivoted on the EmployeeID column.

SELECT PurchaseOrderID, EmployeeID, VendorID  
FROM PurchaseOrderHeader;  

The unique values returned by the EmployeeID column become fields in the final result set. As such, there's a column for each EmployeeID number specified in the pivot clause: in this case employees 250, 251, 256, 257, and 260. The PurchaseOrderID column serves as the value column, against which the columns returned in the final output, which are called the grouping columns, are grouped. In this case, the grouping columns are aggregated by the COUNT function. Notice that a warning message appears that indicates that any null values appearing in the PurchaseOrderID column weren't considered when computing the COUNT for each employee.


When aggregate functions are used with PIVOT, the presence of any null values in the value column are not considered when computing an aggregation.


UNPIVOT carries out almost the reverse operation of PIVOT, by rotating columns into rows. Suppose the table produced in the previous example is stored in the database as pvt, and you want to rotate the column identifiers Emp1, Emp2, Emp3, Emp4, and Emp5 into row values that correspond to a particular vendor. As such, you must identify two additional columns. The column that will contain the column values that you're rotating (Emp1, Emp2,...) will be called Employee, and the column that will hold the values that currently exist under the columns being rotated will be called Orders. These columns correspond to the pivot_column and value_column, respectively, in the Transact-SQL definition. Here's the query.

-- Create the table and insert values as portrayed in the previous example.  
CREATE TABLE pvt (VendorID INT, Emp1 INT, Emp2 INT,  
    Emp3 INT, Emp4 INT, Emp5 INT);  
INSERT INTO pvt VALUES (1,4,3,5,4,4);  
INSERT INTO pvt VALUES (2,4,1,5,5,5);  
INSERT INTO pvt VALUES (3,4,3,5,4,4);  
INSERT INTO pvt VALUES (4,4,2,5,5,4);  
INSERT INTO pvt VALUES (5,5,1,5,5,5);  
-- Unpivot the table.  
SELECT VendorID, Employee, Orders  
   (SELECT VendorID, Emp1, Emp2, Emp3, Emp4, Emp5  
   FROM pvt) p  
   (Orders FOR Employee IN   
      (Emp1, Emp2, Emp3, Emp4, Emp5)  
)AS unpvt;  

Here's a partial result set.

VendorID    Employee    Orders
----------- ----------- ------
1            Emp1       4
1            Emp2       3 
1            Emp3       5
1            Emp4       4
1            Emp5       4
2            Emp1       4
2            Emp2       1
2            Emp3       5
2            Emp4       5
2            Emp5       5

Notice that UNPIVOT isn't the exact reverse of PIVOT. PIVOT carries out an aggregation and merges possible multiple rows into a single row in the output. UNPIVOT doesn't reproduce the original table-valued expression result because rows have been merged. Also, null values in the input of UNPIVOT disappear in the output. When the values disappear, it shows that there may have been original null values in the input before the PIVOT operation.

The Sales.vSalesPersonSalesByFiscalYears view in the AdventureWorks2022 sample database uses PIVOT to return the total sales for each salesperson, for each fiscal year. To script the view in SQL Server Management Studio, in Object Explorer, locate the view under the Views folder for the AdventureWorks2022 database. Right-click the view name, and then select Script View as.

Next steps