SQL Server Performance Optimization as a Database Developer
SQL Server performance
optimization is one of the most debated topics in database management. When
performance issues arise, the first question teams ask is:
To understand the responsibilities as a Database Developer, we must practice below mentioned guidelines for an efficient Database.
Performance Optimization as a Database Developer (Query Level)
1. Write SARGable Queries
What it means:
Queries that can use indexes.
Bad:
WHERE YEAR(OrderDate) = 2024
Good:
WHERE OrderDate >= '2024-01-01'
AND OrderDate < '2025-01-01'
2. Avoid SELECT *
What it means:
Only fetch what you need.
Why it matters:
Reduces I/O and memory.
SELECT OrderID, OrderDate FROM
Orders;
3. Use Set-Based Operations
What it means:
Work on all rows at once.
Bad (RBAR):
WHILE ...
Good:
UPDATE Orders SET Status =
'Closed'
WHERE OrderDate < '2023-01-01';
4. Proper Index Usage Awareness
What it means:
Know which index your query uses.
Why it matters:
Wrong index = slow query.
Example:
Check execution plan → look for Index Seek vs Scan.
5. Efficient Joins
What it means:
Join on indexed columns with matching data types.
Bad:
INT = VARCHAR
Good:
Orders.CustomerID =
Customers.CustomerID
6. Stored Procedures over
Ad-Hoc SQL
What it means:
Precompiled execution plans.
Why it matters:
Less CPU usage.
CREATE PROCEDURE
GetOrdersByCustomer
@CustomerID INT
AS
SELECT * FROM Orders WHERE
CustomerID = @CustomerID;
7. Parameter Sniffing Awareness
What it means:
SQL Server optimizes based on first parameter value.
Problem:
One value fast, another slow.
Fix Example:
OPTION (RECOMPILE)
8. Transaction Management
What it means:
Keep transactions short.
Bad:
BEGIN TRAN
-- user input here
COMMIT
Good:
Only wrap required statements.
9. Avoid RBAR Patterns
What it means:
Row By Agonizing Row processing.
Replace loops with:
- JOINs
- Window functions
ROW_NUMBER() OVER (PARTITION BY
CustomerID ORDER BY OrderDate)
10. Test with Realistic Data
Volumes
What it means:
Small data hides performance problems.
Why it matters:
Execution plans change with size.
Example:
Query runs fast at 1K rows, fails at 10M.
Leave your comments and suggestions as required.
About the author:
I am Vivekanand Jha. I am specialize in database management and optimization, sharing my journey and technical insights here on SQLwithVJ.
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