Increase the Speed of SQL Queries
SQL (Structured Query Language) is a homogeneous programming language that is widely used for organizing relational databases, and for the accomplishment of several operations on the data stored in them. To trace the beginning, it was first created and used in the 1970s, SQL is frequently used by mainly the database managers, as well as by developers who are working in the profile of writing data integration scripts. Data analysts who are looking to set up and run analytical queries also use SQL.
SQL statements can be easily used to retrieve relevant data from any database that exists. To get similar outcomes you are required to write dissimilar SQL queries. For optimum performance, you need to use the queries that are not only best and faster but also efficient. Therefore, you need a SQL query tuning, which is based on the business in addition to the user requirements.
Learn SQL Server in the Easiest Way
- Learn from the videos
- Learn anytime anywhere
- Pocket-friendly mode of learning
- Complimentary eBook available
To write more optimized and high-performance queries, opt for our self-learning courses available at a huge discount.
17 Proven Tips to look out in 2020 to increase the speed of SQL queries
Use Column Names Instead of * in a SELECT Statement
By choosing only the columns that you require, you are dropping the size of the result table substantially thereby decreasing the network traffic and increasing the general performance of your query.
In the below screenshot, you can see how ‘International Journal of Scientific & Technology Research’ has very well explained the concept- 
Try not to use HAVING clause in SELECT statements
The HAVING clause is generally used like a filter and that makes is quite impractical in a SELECT statement. It goes through the final result table of the query analyzing the rows that don’t even meet the HAVING condition. See the concept explained in the below screenshot
Avoid using UPDATE instead of CASE
This problem is very common because using UPDATE has a natural flow that seems rational but it is better to use CASE. An UPDATE statement has to write twofold for every single write to the table and thus slowing your results.
Read: What Is The Difference Between The SQL Inner Join And Outer Joins?
Avoid blind re-use of Code
Many developers tend to copy someone else’s as it pulls the data that they need. The issue is that it pulls much more data than you actually need. Trim the code to your exact needs.
Use an IN predicate when querying an indexed column
The IN-list predicate can be used substantially for indexed recovery and also, the optimizer can sort the IN-list to match the sort sequence of the index, leading to more efficient retrieval.
See the concept explained in the below screenshot by ‘International Journal of Scientific & Technology Research’
Try to pull specific columns that you need
It is quite easy to code all your queries with SELECT* command instead of listing the columns separately every time.
Do pre-stage data
If you already have a report or a procedure that can do analogous joins to large tables, it can be an advantage for you to pre-stage the data by linking the tables ahead of time and persisting them into a table.
Do delete and update process in smaller batches
It helps you increase concurrency because your database can go online quickly.
Read: What Is Average Salary Of Database Admin In Philippine?
Try to use temp tables to improve cursor performance
Cursor operations suffer from speed and block problem. To avoid that try to run them against a temp table.
Avoid nest views
This is because you will end up in a loop where you have views that call views that call views that call views. You will have more data retrieved than is needed.
Try to use table-valued functions
Whenever you put a scalar function in the SELECT list of the query, the function is called for every single row in the result set.
Read: A Comprehensive SQL Server Tutorial Guide for Beginners & Experienced
Use EXISTS command instead of DISTINCT when using table joins for tables with one-to-many relationships
The DISTINCT keyword effectively works by picking all the columns in the table then analyzes any duplicates. In its place, if you use subquery with the EXISTS keyword, you can circumvent having to return an entire table as a result.
Do use stored procedures for ORMs
Stored procedures have quite a lot of benefits. The best ones are that you’re pushing much fewer data across the network; the procedure call is shorter etc.
Avoid using OR in join conditions
Every time when you place an ‘OR’ in the join condition, the query will slow down by at least a factor of two.
SQL Server Training & Certification
- No cost for a Demo Class
- Industry Expert as your Trainer
- Available as per your schedule
- Customer Support Available
Avoid writing functions on the right side of the operator you put
Functions or methods are utilized very frequently with their SQL queries. Rewriting the query by eliminating collective functions will escalate the performance extremely.
Register for a Demo class and get to know how well our certified mentors are giving training and LIVE sessions to learners.
Read: How to Use Like Operator in SQL Server?
Remove any redundant mathematics
There will be instances where you will be performing mathematical queries within an SQL statement. They can really drag on the performance if written wrongly. So removing any preventable math in the statement will make it perform more rapidly.
Do to use UNION ALL instead of UNION
The UNION ALL statement is more rapid than UNION, UNION ALL statement never considers copies, and UNION statement looks for duplicates in a table irrespective of their existence.
Final Words
We hope that these tips will help you write better queries. For more insight, read our other blogs on SQL.. We wish you luck for a shining career with the JanBask Training team and our expert certified mentors!
Read: SQL Developer Resume: Examples, Samples, & Tips (2025)
