SQL Storage Compress - 6.0

SQL Storage Compress

Creating a compressed database: SQL Storage Compress wizard or T-SQL scripting

You can create a compressed version of an existing database using one of two methods:

  • automatically, using the SQL Storage Compress Restore backup to compressed database wizard
  • manually, by writing and executing a T-SQL script using your preferred SQL Server management tool (SQL Server Management Studio, for example)

Whichever method you choose, the same basic principle applies:

The compressed version of an existing database is created by restoring from a backup

If you don't already have a backup of the database you want to compress, you will need to create one before proceeding with either method.

Deciding which method to use

Each method has advantages and disadvantages, but in most cases, using the wizard in the SQL Storage Compress application is the best option.

You should use the wizard (automatic method):

  • if you are using SQL Storage Compress for the first time, and need a simple way to create compressed databases, and to review the space savings you could make
  • if you want avoid having to write your own T-SQL statements from scratch
  • if your requirements for the compressed database are relatively straightforward (for example, you want to compress all the data files rather than a select few)
  • if the backup file you are restoring from is in one of the following formats: native SQL Server, SQL Backup Pro, SQL HyperBac, or Quest LiteSpeed™ (unencrypted)

See the worked examples for further detail.

You should use T-SQL scripting (manual method):

  • if you are familiar with writing T-SQL RESTORE DATABASE commands, and need full control over the command options
  • if your requirements for the compressed database are complex (for example, you only want to compress selected data files)
  • if the backup file you are restoring from is in Quest Litespeed™ encrypted format, or another third-party backup-tool format
  • if you need to create compressed databases as part of a batch or scheduled job

See the worked examples for further detail.

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