Best practices for SQL performance management

Effective SQL performance management is essential for ensuring that an application has optimal performance and provides a positive user experience. Here are some best practices for SQL performance management:

Monitor database performance and tune accordingly: Monitoring and tuning database performance is an ongoing process you need to do (or have done) on a regular basis. This includes monitoring performance metrics such as Locks, waits, sorting, CPU usage, memory usage, and disk I/O, and making adjustments as needed. Tuning database performance can help prevent performance issues and save significant costs.
Optimize problematic SQL queries: Optimizing SQL queries is one of the most important tasks for SQL performance management. 90%+ of database performance issues are caused by poorly written or outdated SQL statements. By optimizing SQL queries, you can reduce the time required to retrieve data, improve overall application performance and significantly reduce resource usage (=cost). Some ways to optimize SQL queries include avoiding retrieval of unneeded data, reducing the number of joins, optimizing joins, avoiding subqueries, and tuning indexes.
Use the right indexing: Indexes can significantly improve SQL query performance by reducing the amount of time required to retrieve data. Too few, too many or the wrong indexes will have a large impact on performance.
Manage database resources: Managing database resources is critical for SQL performance management. This includes monitoring resource usage, such as the buffer pool, thread pools, CPU, memory, and disk bandwidth and disk space, and optimizing resource allocation as needed. Managing database resources can help prevent resource contention and ensure that the database performs as expected.
Keep your technical environment in order. E.g. avoid serialization points, use optimal I/O sizes and keep concurrent data streams separated.
Avoid interference from other workloads. When different workloads share the same resources, make sure they don’t get in each other’s way. Either by separating their peaks in time or by applying Quality of Service (QoS).
Use connection pooling: Connection pooling allows multiple application processes to share a single database connection, reducing the time required to establish new connections.
Use a performance monitoring service: Performance monitoring services can help simplify SQL performance management by providing real-time insights into database performance. These services can help identify performance issues, track resource usage, and provide recommendations for optimizing SQL queries and database performance. Using services instead of tools eliminates the need for deep knowledge in your organization.

By following these best practices for SQL performance management, you can ensure that your application performs optimally and provides a positive user experience. Remember that SQL performance management is an ongoing process that requires regular attention and tuning to ensure that the database performs as expected.

Optimizing SQL queries

Optimizing SQL queries is an essential task for improving SQL performance. Here are some best practices for optimizing SQL queries:

Monitor query performance: Monitoring query performance tells you which queries have (potential) bottlenecks. Don’t just look at the usage of an individual query, but factor in the frequency a query is used. A small query fired multiple times a second will likely use more resources than a larger query run hourly. It's essential to monitor query performance metrics, such as CPU, I/O and memory usage, locking, waits and duration, and optimize any queries that impact performance.
Minimize the use of wildcards: The use of wildcards in SQL queries can significantly impact query performance. Wildcards, such as "%" and "_", cause large number of rows to be fetched, slowing down your queries.
Fetch only the columns you need. Select *, or a select with a large column list is rarely needed. Data frameworks often do this if used with their default configuration. Properly configuring your select and or fetch operation avoids retrieving unused data.
Right size your queries. If you need a lot of records, don’t fetch them one by one in separate queries and if need just a few records, don’t fetch a large dataset. Pay special attention to functionality with pagination, fetch only the pages being viewed.
Don’t use subqueries if a join is possible: Subqueries can be resource-intensive and negatively impact query performance. Optimizers often don’t recognize subqueries as a join causing too much data to be retrieved for the query.
Optimize indexing: Proper indexing can significantly improve query performance by reducing the amount of time required to retrieve data. It's essential to use the right indexing strategies, to ensure that queries run as efficiently as possible.
Use standardized query texts: SQL optimizers recognize when queries have the same text as queries used earlier. They can the reuse the parsing and optimizing, greatly reducing overhead. This implies parameterizing your queries and passing values in the parameters rather than as literals. Standardizing query texts often needs to be done down to the white space level as databases otherwise don’t recognize the match.
Use the right data types: Using the right data types for columns can improve query performance by reducing the amount of storage required and reducing the time required to retrieve data. E.g. storing a boolean in a bigint column is a waste of space and processing time. Storing a date in a datetime field is a waste if the database also supports a date type.
Optimize join operations: Improperly written join operations can be resource-intensive and impact query performance. It's essential to optimize join operations by selecting appropriate join types and using appropriate join conditions to ensure that queries run as efficiently as possible. In some database the order of a join can have a significant impact on performance.
Keep your statistics up to date. All modern databases optimize queries based on statistics. If your statistics are wrong, you queries will not be properly optimized, run longer and use more resources than needed.

These best practices for optimizing SQL queries, will help you significantly improve SQL performance and ensure that queries run as efficiently as possible. Optimize queries on a regular basis to keep your application performing well.