The article gives an overview of Data Compression features in SQL services
Data management isn’t an easy process and server like SQL also might face difficulties if the Data grows exponentially, which it does and then there are backups. Is there any way which could simplify the process and consume comparatively less disk space? This is where Compression feature of SQL server fits it. This article will stress more on…
SQL Server allows its DBAs to use the option of Data Compression to reduce the sizes of their heavy databases, and backup compression which reduces the disk space of backups. The Data compression helps a great deal in improving the performances of Database applications and backups by reducing the disk’s input and output operations. Users can perform Data compression by using SSMS i.e. SQL Server Management Studio (SSMS) and also by Transact-SQL.
In SQL, entire databases aren’t compressed but only their objects like tables stored as heap or index, an indexed view, etc. DBAs need to speculate which objects they wish to compress and the ways. You can turn the compression on and off for the objects to enable or disable compression which is entirely carried out on SQL server engines. Data compression significantly reduces the Data Cache memory which gives space for more cache data. It improves the overall performance. However, data compression often takes up extra CPU cycles.
Data compression can be understood through two different ways which are Row level and Page Level Compression.
Row Level Data Compression
The Row level compression usually reduces the amount of data to be stored in a row. For numeric data types, it stores fixed length numerical datatype and to store CHAR datatype it uses variable length data type. It skips the blank characters or null values and only takes actual characters which reduce much of the space. Thus if a datasheet have so many rows, they can get compressed and may fit in a single data page.
Page Level Data Compression
Comparatively it utilizes more CPU cycles but offers better compression. It also uses row level data compression to empty space and gets maximum rows on a page. Prefix and Dictionary compressions are used to avoid repetitions in the data. These repeated values are stored elsewhere. Prefix compression however works only on one column, dictionary compression can work anywhere on the data page.
Why you should use Data Compression
In the hands of experienced DBAs, data compression can go a long way in saving space and increasing the overall efficiency of SQL databases. Further, an oversized database can cause several issues which compression prevents from occurring.
It is prudent for a DBA to consider which form of compression he or she should use and also minutely evaluate objects before going ahead with a compress operation.
Despite your best efforts and even after enforcing compression, the database can continue to grow. In such scenarios, you would need to consider alternate solutions like using a third party tool to deal with any contingencies.
For companies working on the MS SQL Server database, it is critical that they have a backup and recovery plan in place. To ensure zero data loss, it is vital to invest in an mdf fix tool.
Victor Simon is a data recovery expert in DataNumen, Inc., which is the world leader in data recovery technologies, including repair mdb and sql recovery software products. For more information visit https://www.datanumen.com/