10 Essential Tips for Efficient SQL Query Formatting

Did you know that Amazon was able to reduce its AWS costs for big data processing by 37% over a six-month period by implementing effective query optimization strategies? That is what efficiently written queries can do to your business.

SQL ranks as the third most popular language among professional programmers; thus, optimizing your queries can significantly boost performance, reduce load times, and improve user satisfaction.

This article takes you through the 10 best SQL practices that will help you optimize your queries, drive better results, and keep your business running efficiently. 

General Order of SQL Query Execution

Before you write an SQL query, it's important to understand how SQL is processed behind the scenes. Understanding the general order of query execution helps you write more accurate and efficient queries and avoid common mistakes. 

1. FROM (and JOIN): Identifies the tables involved in your query. 
2. WHERE: Filters the data to narrow down the result set.
3. GROUP BY: Aggregates data based on specified columns.
4. HAVING: Filters out aggregated data that doesn't meet the set criteria.
5. SELECT: Specifies which columns to retrieve 
6. UNION: Combines the results from multiple queries into a single result set.
7. ORDER BY: Sorts the result set based on specified columns.

Understanding this order is vital, as it directly impacts how you write and optimize queries. Now, let us look at 10 SQL best practices you should follow to enhance performance, maintainability, and scalability.

10 Best Practices To Write SQL Queries

Efficient SQL queries can significantly enhance your database performance. Here are the 10 best practices that will help you write clean, efficient, and maintainable SQL queries:

1. Use proper indexing

Indexing is one of the simplest and most effective ways to speed up your queries. By creating indexes on frequently queried columns, you make it easier for the database to find data quickly. However, too many indexes can hamper your performance; therefore, choose them wisely.

Imagine you have a table Employees with a column LastName. If you frequently query this table by LastName, creating an index on that column can significantly improve search performance.

CREATE INDEX idx_lastname ON Employees(LastName);

2. Avoid using SELECT * (Wildcard)

Using SELECT * might seem convenient; however, it’s inefficient in larger databases since it retrieves unnecessary columns, increasing the time taken to process a query. Always specify only the columns you need.

Instead of:

SELECT * FROM Orders;

Use:

SELECT OrderID, CustomerName, OrderDate FROM Orders;

3. Use comments for clarity

Commenting on your SQL code is an important practice that helps you understand and maintain your queries. You can add comments to clarify the purpose of your code, especially for complex queries, making it easier for others (or your future self) to understand. It's also helpful to note why you chose a particular approach or any important details.

In SQL, you can use two types of comments:

1. Single-line comments: Use -- to comment out a single line.
2. Multi-line comments: Use /* ... */ to comment out multiple lines.

Example

-- This query retrieves employee names and salaries from the employees' table

SELECT first_name, last_name, salary FROM employees WHERE department = 'Sales'; 

-- Only employees in the Sales department

4. Utilize query caching

Many SQL databases support query caching, a feature that stores the result of a query for faster subsequent retrieval. This is particularly useful for frequently executed read-only queries.

Depending on your database engine, utilize caching when suitable to lessen the strain on your database.

Example

Caching the results of your query can significantly accelerate subsequent requests if you're running frequent reports on sales data that don't change every minute.

5. Use transactions to manage data integrity

Transactions help manage changes to your database in a way that ensures data integrity. Group related SQL operations into a transaction to ensure all actions are completed successfully or none of them are applied.

Example

Suppose you are transferring funds between two accounts. Use a transaction to ensure that both operations (deducting from one account and adding to the other) are completed successfully. Use ROLLBACK to revert changes in case of a failure, thus ensuring consistency.

BEGIN TRANSACTION;
UPDATE Accounts SET Balance = Balance - 500 WHERE AccountID = 1;
UPDATE Accounts SET Balance = Balance + 500 WHERE AccountID = 2;
COMMIT;

6. Normalize your data

Database normalization is a technique used to reduce redundancy and improve data integrity by organizing your data into separate tables. It facilitates maintenance and ensures consistency across your database. Use foreign keys to relate tables, maintain normalization, and reduce data waste.

Example

Instead of storing customer addresses within every order, store customer information in one table and reference it in the Orders table:

CREATE TABLE Customers ( CustomerID INT PRIMARY KEY, Name VARCHAR(100), Address VARCHAR(200));
CREATE TABLE Orders ( OrderID INT PRIMARY KEY, CustomerID INT, ProductID INT, OrderDate DATE, FOREIGN KEY (CustomerID) REFERENCES Customers(CustomerID));

7. Optimize queries with WHERE clauses

Use WHERE clauses to filter data as early as possible in your queries. The more you can reduce the number of rows returned, the more efficient your query will be. 

Filter out unnecessary data early in your query to boost performance. The database can become overloaded and unresponsive without proper query optimization and index management.

Instead of:

SELECT * FROM Orders;

Use a WHERE clause to narrow down the results:

SELECT OrderID, CustomerID, OrderDate FROM Orders WHERE OrderDate > '2024-01-01';

8. Use batch processing for large data inserts

When inserting large volumes of data, batch inserts are much more efficient than inserting one row at a time. This reduces the number of transactions and improves the overall speed.

Instead of:

INSERT INTO Products (ProductID, ProductName) VALUES (1, 'Laptop');
INSERT INTO Products (ProductID, ProductName) VALUES (2, 'Smartphone');

Use batch processing:

INSERT INTO Products (ProductID, ProductName) VALUES (1, 'Laptop'),(2, 'Smartphone');

9. Use aggregate functions judiciously

Aggregate functions such as COUNT(), SUM(), AVG(), and GROUP BY can be extremely useful; however, they can also slow down your queries if not used correctly. Use them in conjunction with proper indexing and filtering to keep performance high.

Instead of:

SELECT ProductID, SUM(Quantity) FROM Orders GROUP BY ProductID;

Add an index on ProductID to improve performance:

CREATE INDEX idx_productid ON Orders(ProductID);

10. Regularly clean up your database

Database maintenance is crucial for maintaining query performance. Regularly cleaning up your database by removing unnecessary data, rebuilding indexes, and updating statistics ensures your system stays fast and efficient. Schedule regular maintenance tasks to avoid performance degradation over time.

Example

Use commands such as VACUUM or OPTIMIZE to reorganize your database and reclaim space:

VACUUM FULL;

Maximizing Your Database Performance With Acceldata

Optimizing SQL queries is essential as data volumes grow and queries become more complex. This ensures better database performance to support evolving business needs. 

By implementing best practices such as effective indexing, query formatting, caching, and database cleanup, you can ensure responsive databases that meet user needs, even during peak usage. 

Regular cleanup, proactive resource management, and a commitment to optimization and sql tuning play a key role in preventing bottlenecks and maintaining long-term database efficiency.

Acceldata’s observability platform provides invaluable support in maximizing your database performance with query optimization and tuning. With advanced capabilities such as predictive analysis, performance optimization, and AI-driven automations, Acceldata enables businesses to optimize and maintain database responsiveness at scale.

Acceldata empowers organizations to meet modern data challenges by combining SQL best practices with advanced features, ensuring effective database usage and driving business success.

Ready to optimize your SQL performance? Get a demo of the Acceldata platform and discover how to optimize your SQL queries for faster, more efficient results.