Best Practices using INNER JOIN in SQL Server

Aman Raiyyani
Best Practices using INNER JOIN in SQL Server

This is the most commonly used type of join. It returns only the rows that have matching values in both tables. The syntax for an inner join is:

SELECT column1, column2
FROM table1
JOIN table2
ON table1.column = table2.column;

Real-life example: A retail store has a table of customers and a table of orders. To get a list of all orders along with the customer’s name and address, you could use an inner join to combine the data from the customers and orders tables.

SELECT, customers.address, orders.order_id, orders.purchase_date 
FROM customers 
JOIN orders 
ON customers.customer_id = orders.customer_id;

There are several best practices for using inner joins in SQL Server:

Use the ON clause to specify the join condition: The ON clause should be used to specify the condition for the join, rather than using the WHERE clause. This makes the query more readable and ensures that the join is only applied to the specified columns.

Use indexes on join columns: To improve query performance, it is important to have indexes on the columns that are used in the join condition. This allows the database engine to quickly locate the matching rows in both tables.

Use aliases for table names: Using aliases for table names can make the query more readable and make it easier to reference the correct table when there are multiple tables in the query.

Use the INNER JOIN keyword only when necessary: When joining tables, it is best to be explicit and use the INNER JOIN keyword only when it is needed. Because it’s the default join type, it’s not needed to be specified

Be mindful of the order of the tables: The order of the tables in the join can affect the performance of the query. It’s best to put the table with the smallest number of rows first in the join.

Watch out for Cartesian products: When joining tables without specifying a join condition or specifying a non-restrictive condition, it can result in a Cartesian product, where every row from one table is combined with every row of the other table, resulting in a very large number of rows.

Use Explicit Columns: When joining tables, it’s best to be explicit and only select the columns that you need. This can help to reduce the amount of data that needs to be retrieved and processed, which can improve query performance.


SELECT, orders.order_id

FROM customers

JOIN orders

ON customers.customer_id = orders.customer_id;

In this example, the join is done on the customer_id column, and only the name and order_id columns are selected. This improves the readability and performance of the query.

Explore our range of trailblazer services

Risk and Health Audit

Get 360 degree view in to the health of your production Databases with actionable intelligence and readiness for government compliance including HIPAA, SOX, GDPR, PCI, ETC. with 100% money-back guarantee.

DBA Services

The MOST ADVANCED database management service that help manage, maintain & support your production database 24×7 with highest ROI so you can focus on more important things for your business

Cloud Migration

With more than 20 Petabytes of data migration experience to both AWS and Azure cloud, we help migrate your databases to various databases in the cloud including RDS, Aurora, Snowflake, Azure SQL, Etc.

Data Integration

Whether you have unstructured, semi-structured or structured data, we help build pipelines that extract, transform, clean, validate and load it into data warehouse or data lakes or in any databases.

Data Analytics

We help transform your organizations data into powerful,  stunning, light-weight  and meaningful reports using PowerBI or Tableau to help you with making fast and accurate business decisions.

Govt Compliance

Does your business use PII information? We provide detailed and the most advanced risk assessment for your business data related to HIPAA, SOX, PCI, GDPR and several other Govt. compliance regulations.

You May Also Like…