Dynamic SQL: Techniques, Security, and Optimization

In this guide, I will explain the key aspects of dynamic SQL, including essential techniques for crafting and executing dynamic queries, applications, security considerations, performance optimization strategies, and common use cases.

Dynamic SQL is exciting because it is a powerful technique that enables the construction and execution of SQL statements at runtime. Dynamic SQL allows developers to write more flexible and adaptive queries that can respond to different input, conditions, and logic during execution.

If you are new to SQL, consider starting with our Introduction to SQL course or Intermediate SQL course to build a strong foundation. Also, I find the SQL Basics Cheat Sheet, which you can download, is a helpful reference because it has all the most common SQL functions.

What Is Dynamic SQL?

Dynamic SQL refers to SQL statements that are constructed and executed at runtime rather than being hard-coded in advance. This method provides a way to build and run SQL queries based on variable input or logic defined during program execution.

With dynamic SQL, you create SQL statements as strings and execute them using special execution functions or constructs. Unlike static SQL, which is predefined and embedded directly in code, dynamic SQL offers greater flexibility by allowing query structures, such as table names, filter conditions, or sorting logic, to be determined at runtime. This makes it a versatile tool for scenarios where query requirements are not known until the application is running.

Why Use Dynamic SQL?

Modern applications often require database queries that can adapt to changing business needs and user-driven logic. Dynamic SQL is important in enabling more responsive and customizable database interactions.

Common use cases for dynamic SQL include generating reports with optional filters, building search interfaces with customizable parameters, automating repetitive database tasks, and managing objects like tables and indexes programmatically. It allows developers to write powerful and adaptable applications, reducing the need for hardcoded logic. By accommodating changing requirements and supporting user-driven behavior, dynamic SQL is important in environments where flexibility, automation, and data-driven decision-making are priorities.

Dynamic SQL vs. Static SQL

Understanding the differences between static and dynamic SQL is important for choosing the right approach. Below are the key distinctions you should know before selecting either method when executing your queries.

Key differences

Static SQL statements are hardcoded and do not change at runtime. To a data analyst, this means that the statements offer predictable performance and easier maintenance. Dynamic SQL, on the other hand, is constructed and executed at runtime, providing greater flexibility at the cost of increased complexity and potential security risks. I have summarized these differences in the table below.

When to choose dynamic SQL

Dynamic SQL is preferable in scenarios where the query structure cannot be determined until runtime or when high flexibility is required. These include the following:

• Dynamic reporting: When you need to select columns, filters, or sort orders at runtime.

• Variable database objects: When table or column names are determined dynamically, such as in multi-tenant applications or data warehouses with time-partitioned tables.

• Complex search and filtering: When advanced search features require assembling queries based on multiple, user-defined criteria.

• Executing DDL statements: For operations like CREATE, DROP, GRANT, or ALTER, which cannot be performed with static SQL on many platforms.

However, the limitations of using static SQL for dynamic scenarios include the following:

• Inability to handle runtime changes in query structure or database objects.
• Increased code duplication when multiple similar queries are needed.
• Lack of adaptability to user-driven logic reduces application flexibility.

Dynamic SQL in SQL Server, PostgreSQL, and Oracle

Executing dynamic SQL involves creating query strings and using appropriate database functions to run them safely and efficiently. In this section, I outline the main methods and best practices for dynamic execution.

Using EXEC command

Most database platforms provide an EXEC or EXECUTE command to run dynamic SQL.

For example, the following query runs dynamic SQL in SQL Server, although it does not support parameterization, increasing the risk of SQL injection.

-- Declare a variable to hold the SQL statement
DECLARE @sql NVARCHAR(MAX)

-- Build dynamic SQL with a WHERE condition for Department = 'Sales'
SET @sql = 'SELECT * FROM Employees WHERE Department = ''Sales'''

-- Execute the dynamic SQL
EXEC(@sql)

I recommend taking our Introduction to SQL Server and Intermediate SQL Server to learn more about processing data in SQL Server.

For PostgreSQL, the EXECUTE command should be used within a PL/pgSQL code block, like inside a function or DO block. For example:

-- Executes a static SQL string using dynamic SQL (PL/pgSQL context)
DO $
BEGIN
  EXECUTE 'SELECT * FROM employees';
END;
$;

In Oracle, EXECUTE IMMEDIATE cannot directly return result sets from a SELECT statement unless used with INTO or cursors.

-- Executes a dynamic SQL statement (usually DML or DDL) at runtime
DECLARE
  v_count NUMBER;
BEGIN
  EXECUTE IMMEDIATE 'SELECT COUNT(*) FROM employees' INTO v_count;
  DBMS_OUTPUT.PUT_LINE(v_count);
END;

Using sp_executesql and equivalents

SQL Server offers the sp_executesql stored procedure, which allows you to execute dynamic SQL with parameters, improving security and performance:

-- Declare variables to hold SQL command and parameter value
DECLARE @sqlCommand NVARCHAR(1000)
DECLARE @city NVARCHAR(75)

-- Set parameter value
SET @city = 'London'

-- Build parameterized dynamic SQL query
SET @sqlCommand = 'SELECT * FROM Person.Address WHERE City = @city'

-- Execute the query safely using sp_executesql with parameter definition and binding
EXECUTE sp_executesql @sqlCommand, N'@city NVARCHAR(75)', @city = @city

Other databases use a similar construct to reduce the risk of SQL injection and allow for query plan reuse. For example,

• Oracle: EXECUTE IMMEDIATE

• PostgreSQL: EXECUTE within PL/pgSQL

Using parameterized queries safely

Parameterized execution prevents SQL injection by separating query logic from user input. For example, the query below uses sp_executesql to allow parameterization.

-- Declare a variable to hold the dynamic SQL query and initialize Employee ID
DECLARE @sql NVARCHAR(MAX), @empId INT = 1001;

-- Build parameterized SQL query using a named parameter (@ID)
SET @sql = 'SELECT * FROM Employees WHERE EmployeeID = @ID';

-- Execute the SQL query securely using sp_executesql with parameter declaration and binding
EXEC sp_executesql @sql, N'@ID INT', @ID = @empId;

How to Build a Dynamic SQL Statement

Now that you have learned the different methods of executing dynamic SQL queries, let me walk you through an example of building and executing the dynamic SQL command. The queries below are executed in SQL Server.

Step 1: Define the variables

Set up variables to dynamically filter rows from the Employees table based on the Department column with a value of 'Sales'.

-- Prepare dynamic SQL variables to filter the Employees table
DECLARE @tableName NVARCHAR(100) = 'Employees';
DECLARE @filterColumn NVARCHAR(100) = 'Department';
DECLARE @filterValue NVARCHAR(100) = 'Sales';
DECLARE @sql NVARCHAR(MAX);

Step 2: Build the SQL statement

Build a parameterized dynamic SQL query that selects all records from a specified table where a given column matches a value.

-- Construct a safe dynamic SQL query with table and column names 
-- Use QUOTENAME to prevent injection.
SET @sql = 
  'SELECT * FROM ' + QUOTENAME(@tableName) + 
  ' WHERE ' + QUOTENAME(@filterColumn) + ' = @val';

Step 3: Execute with a parameter

Now execute the dynamic SQL query with a parameter @val safely bound to the filter value 'Sales'.

-- Execute the dynamic query with @val parameter securely passed as 'Sales'.
EXEC sp_executesql @sql, N'@val NVARCHAR(100)', @val = @filterValue;

I recommend taking our course, Writing Functions and Stored Procedures in SQL Server, to understand the structure and order of SQL functions for optimized queries.

Security Considerations and Mitigation Strategies

While dynamic SQL introduces flexibility, it also comes with increased risk, particularly related to SQL injection. Let us discuss the common vulnerabilities and best practices to safeguard dynamic SQL usage.

SQL injection vulnerabilities

String-based dynamic SQL is particularly vulnerable to SQL injection, where malicious input alters the intended logic of a query. Attackers can exploit poorly constructed SQL to manipulate data, extract sensitive information, or damage database integrity.

For example, the following query is vulnerable to SQL injection because it directly concatenates user input into the SQL string without parameterization.

DECLARE @sql NVARCHAR(MAX) = 'SELECT * FROM Users WHERE Username = ''' + @input + '''';
EXEC(@sql);
-- If @input = 'admin' OR '1'='1', this returns all users.

Defense-in-depth approaches

The following are methods for ensuring security measures are in place for your dynamic SQL queries:

• Parameterization: Using parameterized queries is the most effective defense. It ensures user input is treated strictly as data, not executable code.

• Object sanitization: When table or column names must be dynamic, validate them against known allowed lists and use functions like QUOTENAME() to prevent injection.

• Principle of least privilege: Restrict database user permissions so that accounts used for dynamic SQL have only the minimum access required. This limits the damage possible if a vulnerability is exploited, reducing the risk of unauthorized data exposure or modification.

• Input validation: Always validate and constrain user inputs to expected formats and values before using them in SQL statements. Reject or sanitize inputs that do not conform, further reducing the attack surface.

Performance Optimization Techniques

Dynamic SQL can cause performance overhead due to runtime compilation and plan generation. To improve the performance of your dynamic SQL queries, I recommend the following query optimization techniques.

Plan caching and reuse

When dynamic SQL is executed, the database engine may cache the execution plan for reuse, improving performance for repeated queries. However, plan reuse is most effective when queries are parameterized rather than constructed with unique SQL strings each time.

Using constructs like sp_executesql with parameters enables the database to recognize similar queries and reuse execution plans, reducing compilation overhead and improving efficiency. SQL Server allows plan guides to be attached to dynamic SQL, influencing optimization and execution plans for better performance in complex scenarios.

Batch optimization

Combining multiple operations into a single execution batch can reduce the number of round-trips between the application and database, decreasing transactional overhead and improving throughput.

Maintenance and Debugging Strategies

Due to its runtime nature, maintaining and debugging dynamic SQL can be more complex than static SQL. The following are practical strategies I recommend for logging and error handling to improve visibility, traceability, and reliability.

Execution logging

Logging the execution of dynamic SQL is important for both auditing and troubleshooting. Capturing the exact SQL statements that run, especially when they are generated at runtime, helps identify performance bottlenecks, unexpected logic, and security issues. Follow these practices to ensure proper logging strategies:

• Audit trails: Implementing logging mechanisms, such as audit tables or triggers, helps record dynamic SQL executions and data changes. 
• Troubleshooting: By storing executed SQL statements, input parameters, execution times, and user information, teams can more easily identify the source of errors, performance bottlenecks, or unauthorized access.
• Performance monitoring: Execution logs can be analyzed to detect slow-running queries, frequent execution patterns, or resource-intensive operations, supporting proactive performance tuning.

Error handling

Dynamic SQL execution should be wrapped in robust error-handling logic to capture and gracefully respond to failures. For example, the following query logs useful diagnostic information to a table.

BEGIN TRY
    -- Attempt to execute the parameterized dynamic SQL
    EXEC sp_executesql @sql, @paramDef, @paramVal;
END TRY
BEGIN CATCH
    -- On error, log the message, line, and procedure name with timestamp into ErrorLog table
    INSERT INTO ErrorLog (ErrorMessage, ErrorLine, ErrorProcedure, LoggedAt)
    VALUES (ERROR_MESSAGE(), ERROR_LINE(), ERROR_PROCEDURE(), GETDATE());
END CATCH;

Also, consider the following practices for error handling:

• Always capture the full error context: message, line number, procedure, and timestamp.
• Use logging to correlate errors with the exact SQL that caused them.
• In production systems, consider alerting mechanisms based on logged errors.

Conclusion

To fully utilize dynamic SQL, developers must adopt strong security practices. Performance should also be carefully managed through plan reuse, batching, and execution logging. Additionally, consider a balanced approach that combines the safety and speed of static SQL with the adaptability of dynamic SQL.

Looking ahead, improvements in database engines, such as smarter execution plans and advanced SQL runtime features, promise to make dynamic SQL more efficient, secure, and easier to manage at scale. As a next step, take our Associate Data Analyst in SQL career track and subscribe to the DataFramed podcast, which features great episodes, like this one featured the co-inventor of SQL: 50 Years of SQL with Don Chamberlin.