Definition: 

Dynamic SQL refers to the process of constructing and executing SQL statements at runtime, rather than hardcoding them in the source code. This allows you to generate SQL statements based on runtime conditions such as user input or other external factors, making your application more flexible and adaptable. Dynamic SQL can be implemented in various programming languages and database management systems, and it’s often used in situations where the SQL statement cannot be determined at compile time.  

How Dynamic SQL works: 

  • In dynamic SQL, variables are used to hold dynamic values that can change during the execution of a program. For example, a variable can be used to hold a user ID or a search term that is used to build a dynamic query.  
  • Concatenation is the process of joining two or more strings together to create a new string. In dynamic SQL, concatenation is often used to build SQL statements based on user input or other dynamic factors. 
  • Placeholders are special markers in a SQL statement that are replaced with actual values at runtime. Placeholders are important because they allow for the separation of the SQL statement from the values that are being passed into it. This can help to prevent SQL injection attacks.  

Advantages of Dynamic SQL: 

  • Flexibility: Dynamic SQL allows you to construct SQL statements based on dynamic conditions. This means that you can change the SQL statement on the fly depending on the user’s input or other runtime factors. For example, you could use dynamic SQL to construct a search query where the user can select from a range of search criteria, such as date range, keyword, and location. Dynamic SQL allows you to construct the query based on the selected search criteria, which makes your application more flexible and responsive. 
  • Code Reusability: Dynamic SQL can help to improve code reusability. You can write a generic SQL statement, and then use dynamic SQL to modify it for different scenarios. This means that you don’t need to write multiple SQL statements for different scenarios, which can save time and effort. For example, you could write a generic SQL statement that retrieves data from a specific table, and then use dynamic SQL to modify the statement to retrieve data from different tables. 
  • Reduced Repetitive Coding: Using dynamic SQL can eliminate the requirement for writing redundant code. By creating a generic SQL statement, you can modify it with dynamic SQL to suit different situations. This eliminates the necessity of writing multiple SQL statements for comparable situations, thus saving time and effort. For instance, you can generate a universal SQL statement to extract data from a specific table and apply dynamic SQL to alter the query to retrieve data with various filters or conditions. 
  • Improved Performance: Dynamic SQL can help to improve performance in some cases. For example, if you have a complex query with multiple joins and conditions, you can use dynamic SQL to build the query based on the user’s input. This means that you can avoid executing unnecessary joins and conditions, which can improve performance. 

Limitations of Dynamic SQL: 

  • Increased Complexity: Dynamic SQL can add an extra layer of complexity to your code. With dynamic SQL, you must generate SQL statements at runtime, which can be difficult to debug and maintain. The complexity of dynamic SQL can also make it harder for other developers to understand and modify your code. 
  • Security Concerns: Dynamic SQL can pose security risks if not implemented correctly. Attackers can exploit vulnerabilities in dynamic SQL to inject malicious code or conduct SQL injection attacks. Proper security measures such as input validation, parameterization, and least privilege should be implemented to mitigate these risks. 
  • Maintenance Overhead: With dynamic SQL, you need to maintain not only the application code but also the dynamic SQL code. Any changes made to the underlying database schema or query logic can break the dynamic SQL code, requiring additional maintenance overhead. 
  • Performance Issues: Dynamic SQL can also impact application performance. Generating SQL statements at runtime can result in additional processing overhead, and execution plans may not be cached, resulting in slower query performance. Additionally, dynamic SQL can lead to inefficient query plans that may not leverage indexes or other performance optimizations. 

Example: 

Level 1:  

DECLARE  
                   @CustomerID INT = 1,   
                   @StartDate DATE = ‘2006-08-25’, 
                   @EndDate DATE = ‘2008-04-09’; 
SELECT  
              OrderID,  
             OrderDate, 
            Custid 
FROM 
             Sales.Orders 
WHERE 
            CustID = @CustomerID 
 AND  
OrderDate BETWEEN @StartDate AND @EndDate; 

(In this example, we declared three variables, to retrieve orders for a specific customer and date range between start and end date) 

Result: 

Level 2: Dynamic Stored Procedure 
CREATE PROCEDURE GetCustomers 
                                                  @sortColumn VARCHAR(50), 
                                                   @sortOrder VARCHAR(4) 
AS 
BEGIN 
             DECLARE 
                        @sql NVARCHAR(MAX); 
 SET 
            @sql = ‘SELECT * FROM [HR].[Employees] ORDER BY ‘ + @SortColumn + ‘ ‘ + @SortOrder; 
             EXEC sp_executesql @sql; 
END 

(In this example, we are creating a stored procedure that takes two input parameters: @sortColumn and @sortOrder. These parameters are used to dynamically create a SQL query that will sort the results of the Customers table. The sp_executesql system stored procedure is used to execute the dynamically created SQL query.) 

(In object explorer extend your database, in programmability we can find our dynamic sp) 

Calling Dynamic stored procedure 

EXEC GetCustomers @sortColumn = ‘LastName’, @sortOrder = ‘ASC’; 

Conclusion: 

Some key benefits of dynamic SQL include the ability to create more flexible and adaptable queries, improved performance by reducing the amount of data retrieved from the database, and the ability to create more efficient queries by leveraging the database’s optimizer. 

However, there are also potential pitfalls to using dynamic SQL, including security risks such as SQL injection attacks, increased complexity in query design, and the potential for performance issues due to inefficient query generation. 

To avoid these pitfalls, it’s important to carefully consider the design of dynamic SQL queries, including input validation and parameterization to prevent SQL injection attacks, and optimization techniques such as caching and reuse of query plans.