Data compression sql server performance

How can I speed up my SQL Server performance?
Tips to improve SQL Server performance & database design
1. Choose Appropriate Data Type
2. Avoid nchar and nvarchar
3. Avoid NULL in the fixed-length field
4. Avoid * in SELECT statement
5. Use EXISTS instead of IN
6. Avoid Having Clause
7. Create Clustered and Non-Clustered Indexes
8. Keep clustered index small
What are the limitations of compression in SQL Server?
Compression can allow more rows to be stored on a page, but doesn't change the maximum row size of a table or index.
A table can't be enabled for compression when the maximum row size plus the compression overhead exceeds the maximum row size of 8,060 bytes..

For rowstore tables and indexes, use the data compression feature to help reduce the size of the database. In addition to saving space, data compression can help improve performance of I/O intensive workloads because the data is stored in fewer pages and queries need to read fewer pages from disk.

Generally data compression reduces the space occupied by the data. Data compression can help improve performance of I/O intensive workloads because the data is stored in fewer pages and queries need to read fewer pages from disk. Data compression can be performed for a table, clustered index, non-clustered index.

Is there a risk of plan regression when using data compression in SQL Server?

This can lead to reduced I/O and better performance.
However, it can also result in additional CPU usage in some cases, outweighing the benefits of data compression.
SQL Server query optimizer does not cost the overhead of expanding the compressed data, which can lead to plan regression as shown in the video.

What are the benefits of using data compression in SQL Server?

In addition to saving space, data compression can help improve performance of I/O intensive workloads because the data is stored in fewer pages and queries need to read fewer pages from disk.
However, extra CPU resources are required on the database server to compress and decompress the data, while data is exchanged with the application.

Examining Query Performance

Before we test query performance

Summary

The additional CPU required to retrieve compressed data exists and can be measured using Query Store or traditional baselining methods

How effective is data compression in SQL Server?

On average, data compression in SQL Server can reduce your data size by 40%

In some cases, it could be so effective that you could achieve as much as a 90% reduction in size! But, if you try compressing the wrong table or index, you could compress absolutely nothing, and yet still have to pay the price in the form of higher CPU utilization

How to increase SP_estimate_data_compression_savings in SQL Server 2022?

In SQL Server 2019, sp_estimate_data_compression_savings was enhanced by adding the COLUMNSTORE and COLUMNSTORE_ARCHIVE compression types as options

SQL Server 2022 will add XML compression as an option

You should run the entire query at once, after you have supplied your own values

Data compression can be a huge win for many SQL Server workloads. It can reduce both your required disk I/O and your memory usage at the cost of some added CPU usage in some scenarios. This post gives you a script you can use for estimating data compression savings in SQL Server.