Identifying SQL performance issues

Common causes of SQL performance issues

Not rightsizing your queries: We see both queries that fetch much more data than is needed and the use of many micro queries where a single larger one would be much more efficient.
Do everything queries: An attempt is made to cover too much functionality in a single query.
Poor indexing: Improper or inadequate indexing can lead to slow query performance as the database has to scan through large amounts of data. Over-indexing can cause updates and inserts to slow down significantly, because all those indexes need to be updated when the data changes.
Inefficient SQL Queries: Poorly written queries that are not optimized for the database schema and structure can cause slow performance.
Blocking Lockings : SQL transactions that lock records, pages or tables for extended periods of time severely affect other processes that need access to that data resulting in longer wait times. Locking records that are not going to be updated is a common mistake that causes long delays.
Database fragmentation: As a result of frequent changes like adding or deleting rows in tables within the database without proper maintenance, fragmentation occurs leading to slower querying times due to increased I/O operations on disks.
An inefficient data model. Data models that are theoretically more correct often lead to more complex, slower, queries.
Lack of server resources: When queries are not optimized, they can require more resources than your server has available. Or require the wrong type of resources, such as reading large amount of data from disk instead of from memory.
Bad statistics. Modern SQL databases optimize queries based on statistics of data and indexes. If the statistics are outdated or wrong, even a good SQL statement will have bad performance.

Techniques for identifying performance bottlenecks

Performance bottlenecks can significantly impact the overall performance of a system or application. Therefore, it's essential to identify and address them. Here are some techniques for identifying performance bottlenecks:

Monitoring: Monitoring involves continuously collecting and analyzing performance metrics to identify potential bottlenecks. You should set up alerts to notify you when specific metrics exceed predefined thresholds, allowing you to quickly address potential performance issues.
Profiling: Profiling is the process of analyzing the application's performance to identify where the performance bottlenecks are located in the code or SQL statements. It involves using a profiling tool to collect performance metrics such as CPU usage, memory usage, and network activity spent on specific functionality, such as a SQL statement. Once collected, you can analyze the data to identify where potential and already occurring bottlenecks are located.
Creating execution plans. Profiling tells you which SQL statement is a bottleneck. An execution plan tells you why it is a bottleneck and how to fix it.
Load testing: Load testing involves simulating a representative peak workload on the system or application to identify performance bottlenecks under stress conditions. Load testing can help identify issues such as slow response times, CPU or memory overutilization, and database connection issues.
Code reviews: Code reviews can help identify potential performance issues early in the development process. Developers can review the code for inefficient algorithms, unnecessary database queries, and other performance issues.
Check and optimize your technical environment. Make sure you have at least implemented all best practices from the vendor.