Best practices for indexing

dbForge Studio for SQL Server includes tools that help optimize database performance. This topic describes how to improve SQL query performance by using indexes.

Performance optimization overview

Slow database performance is most often caused by inefficient SQL queries. By understanding where queries slow down or which parts of the database are underperforming, you can apply targeted and effective optimization strategies - specifically through the use of indexing.

Database performance optimization involves the following key steps:

1. Identify performance issues such as high CPU usage, excessive I/O, or memory bottlenecks.

2. Determine the root causes of the bottlenecks.

3. Apply indexing techniques to improve query performance.

This topic describes each step in detail, using dbForge Monitor, Query Profiler, and other tools in dbForge Studio for SQL Server.

Identify performance issues

dbForge Monitor allows you to monitor database performance in real-time by collecting comprehensive system and performance data.

To analyze performance and view the queries that consume the most CPU, memory, and I/O resources, navigate to the Top Queries tab.

Analyze using Monitor

Determine the root causes of bottlenecks

After identifying resource-intensive queries, use Query Profiler to examine query execution details.

  • Plan Diagram — Shows the query execution plan with the cost of each operation, expressed as a percentage of the total batch cost. Hover over nodes to see metrics such as estimated rows, I/O cost, and CPU usage.

Analyze bottlenecks with the Query Profiler plan diagram

  • Plan Tree — Lists each operation with I/O and CPU usage. High resource usage may indicate table scans, nested loops, or missing indexes.

Analyze bottlenecks with the Query Profiler plan tree

Improve performance using indexes

After you identify performance issues related to indexing, apply indexing techniques to improve query efficiency.

Optimize queries with targeted indexes

When the analysis shows that a query lacks an index, create an index to improve execution speed. Focus on high-selectivity columns—columns with a high number of distinct values compared to the total rows in the table. Indexing these columns can help SQL Server quickly narrow search results and reduce full table or index scans.

Columns used in WHERE, JOIN, ORDER BY, or GROUP BY clauses often benefit the most from indexing. Proper indexing reduces I/O and CPU usage, improving database responsiveness.

You can use the Table Editor tool to create an index on the required column(s).

The results show that adding an index significantly improves the performance of queries on high-selectivity columns.

Optimize queries with indexes on columns

For more information about how to create efficient indexes, see Index architecture and design guide.

Avoid overusing indexes

While indexes can improve query performance, excessive indexing can:

  • Increase storage requirements.

  • Slow down data modifications (INSERT, UPDATE, DELETE) because each related index must be updated.

To identify high-selectivity columns and detect potentially redundant indexes, you can use the AI Assistant in dbForge Studio for SQL Server.

The AI Assistant reviews the query structure, analyzes column usage and data distribution, and suggests indexing improvements.

Optimize queries with AI Assistant

Automate index defragmentation

Regular index defragmentation helps maintain performance. You can automate defragmentation by using the CLI Index Manager in dbForge Studio for SQL Server.

Tip

To minimize impact on database performance during peak hours, schedule index defragmentation to run automatically during off-hours.

To schedule index defragmentation:

Step 1: Create an index defragmentation command using CLI Index Manager.

dbforgesql.com /analyzeindex /connection:"Data Source=SERVER;Encrypt=False;Integrated Security=False;User ID=USER; Password=PSW" /database:DB /minindexsize:100 /reorganizethreshold:10 /rebuildthreshold:30 /tempdbsort:Yes /indexrebuildonline:No

dbForge Index Manager defragmentation scan

Step 2: Create a batch file via the Index Manager wizard.

dbForge Index Manager defragmentation fix

Step 3: Schedule the index defragmentation task in Windows Task Scheduler.

Index defragmentation task: set frequency

Recommendations

In addition to using dbForge Studio for SQL Server tools, such as dbForge Monitor, Query Profiler, and Table Editor, you can follow these recommendations to effectively optimize database performance by using indexes.

Indexing Best Practice Description
Maintain balanced performance Ensure optimal balance between read and write operations.
Limit indexes Limit each table to a maximum of five indexes.
Avoid overindexing Avoid creating unused indexes. Ensure that all indexes are used by queries.
Use an appropriate type of index Create composite indexes when queries use multiple columns.
Avoid duplicate indexes Don’t create duplicate indexes on the same columns.
Avoid overusing indexes Avoid using indexes on small tables.
Monitor index size Review index sizes. Compress indexes that are too large.
Identify missing indexes Regularly check new queries for missing indexes.
Defragment indexes Defragment indexes regularly using dbForge Index Manager.
Update statistics Keep statistics up-to-date to ensure that Query Optimizer selects the best execution plans.
Test performance Test execution performance after modifying the database schema or changing indexes to detect slowdowns and revert changes if necessary.
Test applied changes Always test changes only in a development environment.
Back up a database Before updating data, back up your database.
Keep track of changes Use dbForge Source Control to manage and track database changes. The tool records who made updates, when they occurred, and why.
Compare schemas effectively Use dbForge Schema Compare when changes are not under version control and the previous database version exists only as a script or in a backup.