Sql Server Recover Data From Transaction Log – DbForge Transaction Log for SQL Server is a transaction log reader and .ldf file viewer. With it, you can view, analyze, and restore data from SQL Server transaction logs. The tool provides detailed information about all changes in the database and provides the ability to roll back unwanted transactions at different levels depending on the needs.
In the transaction log, SQL Server transactions are displayed, grouped, and sorted in a custom high-performance grid with advanced filtering options.
Sql Server Recover Data From Transaction Log
Check the transaction log for deleted and corrupted data in SQL Server databases. Roll back unintentional or malicious database transactions to repair data. Recovery from specific data loss or corruption without relying on full database recovery.
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User, date, object, type of change, etc. Isolate specific SQL Server transactions Use advanced grid search algorithms, including regular expressions, transaction details, and trail log searches.
Display transaction log information over the network or exported directly to the database, with the ability to later implement it when the database is moved online to SQL script, SQL Bulk files, or online.
Find out who made the changes and their specific entry, as well as when the changes were made, even before the transaction log was set up. In-depth information is available for each operation and transaction recorded in the transaction log.
A transaction log reader helps you get detailed information about changes in SQL Server databases. You can track who made changes, what changed as a result, and when those changes occurred. A complete history of data changes will also be available – from the moment of initial entry of accurate data to all subsequent updates or deletions.
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Restoring an entire database or even tables can sometimes result in data loss, as unwanted changes often affect very small parts of your database. The transaction log allows changes to be rolled back at the row level with high precision. With this feature, you can protect even data that may be lost during recovery at the object level.
After successfully identifying the unwanted change information, you’ll want to restore the database to before the change. Identify and isolate fraudulent transactions and easily modify them to repair damaged data and prevent further data loss at multiple levels.
Restore the state of the database to a specific point in time when it was stable. You can also select specific schedules so that recovery scripts do not affect others.
Easily extract DML (Data Manipulation Language) operations such as INSERT, UPDATE and DELETE from data files, secondary data files and log files.
Intelligent Transaction Log Backups
After creating a script, you can run it immediately or export it to an SQL document for further execution.
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Recovery Models In Sql Server
A recovery model is a database property that defines how SQL Server Engine processes database transaction logs, including logs.
There are three recovery types in SQL Server: full, bulk log, and simple recovery patterns. To understand the recovery models in depth, we will discuss each recovery model individually in relation to the SQL Server transaction log.
The newly created database recovery pattern is the same as the system sample database recovery pattern. Using SQL Server Management Studio, you can change the recovery pattern of an existing database from the Settings page of the Database Properties window.
To do this, right-click on the database and select “Properties”. From the Database Properties window, go to the Settings page and select a new database recovery template from the Recovery Template drop-down list, as shown below:
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When a database is configured with the Simple Recovery model, the SQL Server engine stores SQL transaction logs in the transaction log file for a short period of time while the transaction is active. After SQL Server has written the transaction log entries from the buffer cache to the SQL transaction log file on disk, the log is flushed when a checkpoint operation is performed to commit the transactions. For more information about checkpoints, check Database checkpoints.
A database with a simple recovery model supports only two types of backups: full backups and differential backups, where a SQL Server Transaction Log backup is not available. For a simple recovery model, this can be considered an advantage because with a simple recovery model, the process of managing and maintaining databases is simple, and it handles SQL transaction log file truncation and usage automatically.
This scenario is not always optimal because not being able to back up the SQL Server transaction log for the database means that there is a greater chance of data loss with the Simple database recovery model because a damaged database cannot be recovered with Simple. Recovery pattern up to a certain time. Instead, you can only restore it to the point of a full backup or differential backup.
For example, let’s say the last full backup was taken today at 12 AM, the last differential backup was taken at 12 PM, and the database crash occurred at 6 PM. All database changes made in the last 6 hours will be discarded. Loss of large amounts of data is not suitable for transaction processing systems. In some cases this may be appropriate for read-only or development databases with minimal potential data changes unless you increase the frequency of full or differential backup operations, which is often impossible due to backup performance. additional goals.
Why Is My Sql Log File Huge?
On the other hand, a database with a simple recovery model cannot participate in high availability and disaster recovery solutions such as log shipping, database replication, and always-on availability groups because SQL transaction logs are not stored per SQL Server transaction. . log file after the transaction is executed.
If the database is configured with a full recovery model, after the SQL Server Engine commits a transaction and performs a checkpoint operation, the transaction logs in the SQL transaction log file are kept inactive and are not truncated until the SQL transaction log is backed up. .
On the administrative side, additional effort is required to monitor and manage the size of the SQL transaction log file and prevent it from running out of space or filling up disk drives. This can be done by automating the SQL transaction log backup standby plan to reduce the inactive portion of the SQL transaction log and include it in a full backup strategy with full and differential backup jobs. For more information about managing the SQL transaction log, see Managing the SQL Server Transaction Log.
If you keep an open mind, you’ll see that there’s a big payoff behind that extra effort. Storing transaction log entries in a SQL transaction log file allows us to create high availability and disaster recovery solutions for this database, such as database replication, log shipping, or always-on availability groups.
Restore A Database From A Backup
In addition, backup files created from a comprehensive backup strategy plan consisting of full, differential, and SQL transaction log backups and scheduled based on the company’s disaster recovery plan can be easily used to restore the database in time. Timely, in case of database failure or corruption. With a compatible schedule of three types of backups, any chance of data loss is minimized or completely avoided, making it the best choice for production environments.
In the example discussed earlier, the last full backup is taken at 12 AM, the last differential backup is at 12 PM, and the last hourly SQL transaction log backup is at 6 PM. If the database crashes at 18:05, and with the last full backup, last differential backup, and SQL transaction log backup restored between 12:00 and 18:00, the data loss is only the changes made in the last 5 changes. be as shown below, minutes instead of 6 hours of data loss, which is acceptable in a production environment:
A third recovery pattern that is less commonly used in SQL Server is the bulk log recovery pattern. This is a special-purpose recovery model in which SQL Server Engine processes transaction logs as described in the Complete section.
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