Log shipping: Difference between revisions
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In [[Microsoft SQL Server]], '''log shipping''' is the process of automating the backup of a [[database]] and [[transaction log]] files on a primary (production) server, and then restoring them onto a standby server<ref name="logshipping">[http://www.sql-server-performance.com/articles/clustering/log_shipping_70_p1.aspx How to Perform SQL Server Log Shipping], "What is Log Shipping". Retrieved on 2008-12-16.</ref>. Similar to [[Replication (computer science)|replication]], the primary purpose of log shipping is to increase database availability by maintaining a backup server that can replace production server quickly. |
In [[Microsoft SQL Server]], '''log shipping''' is the process of automating the backup of a [[database]] and [[transaction log]] files on a primary (production) server, and then restoring them onto a standby server<ref name="logshipping">[http://www.sql-server-performance.com/articles/clustering/log_shipping_70_p1.aspx How to Perform SQL Server Log Shipping], "What is Log Shipping". Retrieved on 2008-12-16.</ref>. Similar to [[Replication (computer science)|replication]], the primary purpose of log shipping is to increase database availability by maintaining a backup server that can replace production server quickly. |
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Although the actual [[failover]] mechanism in log shipping is manual, this implementation is often chosen due to its low cost in human and server resources, and ease of implementation. As comparison, SQL server [[computer cluster|cluster]]s enable automatic failover, but at the expense of much higher storage and license costs. Compared to database replication, log shipping does not provide as much reporting capabilities, but backs up also system tables along with data tables, and locks standby server from users' modifications. A replicated server, can be modified (e.g. [[view (database)|view]]s) and therefore is not suitable for failover purposes. |
Although the actual [[failover]] mechanism in log shipping is manual, this implementation is often chosen due to its low cost in human and server resources, and ease of implementation. As comparison, SQL server [[computer cluster|cluster]]s enable automatic failover, but at the expense of much higher storage and license costs. Compared to database replication, log shipping does not provide as much reporting capabilities, but backs up also system tables along with data tables, and locks standby server from users' modifications.<ref>{{cite web|url=http://www.sqlservercentral.com/articles/Replication/logshippingvsreplication/1399/|title=Log Shipping vs Replication|work=SQLServerCentral.com|accessdate=2009-08-07}}</ref> A replicated server, can be modified (e.g. [[view (database)|view]]s) and therefore is not suitable for failover purposes. |
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==References== |
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==External links== |
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Revision as of 09:13, 7 August 2009
In Microsoft SQL Server, log shipping is the process of automating the backup of a database and transaction log files on a primary (production) server, and then restoring them onto a standby server[1]. Similar to replication, the primary purpose of log shipping is to increase database availability by maintaining a backup server that can replace production server quickly.
Although the actual failover mechanism in log shipping is manual, this implementation is often chosen due to its low cost in human and server resources, and ease of implementation. As comparison, SQL server clusters enable automatic failover, but at the expense of much higher storage and license costs. Compared to database replication, log shipping does not provide as much reporting capabilities, but backs up also system tables along with data tables, and locks standby server from users' modifications.[2] A replicated server, can be modified (e.g. views) and therefore is not suitable for failover purposes.
References
- ^ How to Perform SQL Server Log Shipping, "What is Log Shipping". Retrieved on 2008-12-16.
- ^ "Log Shipping vs Replication". SQLServerCentral.com. Retrieved 2009-08-07.
External links
- Log Shipping, MS SQL Server implementation.
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