The SysTools SQL Log Analyzer Tool is an advanced tool for your PC. It allows you to thoroughly examine your SQL Server tables (MDF/NDF) and accurately trace the history of deleted records. Additionally, it helps you recover lost database objects such as triggers, tables, stored procedures, and functions with ease. The tool can open, analyze, and read all MS SQL Server transactions including INSERT, DELETE, and UPDATE. It also allows SQL users to connect to the Online MS SQL Server Database using login credentials to automatically fetch SQL records and data. Users can utilize it for forensic analysis to keep track of detailed changes made to the SQL table records. The application offers three different export options: CSV file, SQL Server database, and SQL Server Compatible Scripts. It keeps track of all transactional activity in the MS SQL Server database.
We are highly confident that SQL users will find the perfect solution to their database recovery needs after familiarizing themselves with the capabilities of this tool.
Here are the steps to follow:
1. Download and launch the software.
2. Add the .ldf/.mdf file.
3. Choose Online or Offline DB Option.
4. Select the SQL database for monitoring.
5. Start the scan process to display transactions.
6. Review the transactional activity in the preview panel.
7. Identify the user involved in each transaction.
8. Export transactions to the SQL Server Database in CSV format or as an SQL Server Compatible Script.
We are highly confident that SQL users will find the perfect solution to their database recovery needs after familiarizing themselves with the capabilities of this tool.
Here are the steps to follow:
1. Download and launch the software.
2. Add the .ldf/.mdf file.
3. Choose Online or Offline DB Option.
4. Select the SQL database for monitoring.
5. Start the scan process to display transactions.
6. Review the transactional activity in the preview panel.
7. Identify the user involved in each transaction.
8. Export transactions to the SQL Server Database in CSV format or as an SQL Server Compatible Script.