Relational databases ensure fault tolerance through several mechanisms that protect data integrity and availability in the event of failures. One primary method is the use of transaction management, which follows the ACID properties—Atomicity, Consistency, Isolation, and Durability. This means that each transaction is treated as a single unit that either fully completes or does not take effect at all, ensuring that partial updates do not corrupt the database. For instance, if a power failure occurs during a money transfer transaction, the database will prevent any changes from being committed until the entire operation is successfully completed.
Another important technique is backup and recovery systems. Regular backups allow a database to restore its data to a consistent state in the event of hardware failure or data corruption. For example, a database can be configured to take incremental backups every few hours and full backups daily. If an issue is detected, administrators can quickly revert to the last good backup, minimizing data loss. Additionally, many relational databases offer features such as point-in-time recovery, which allows users to restore the database to a specific moment, providing even more granularity in recovery options.
Replication is another key method for enhancing fault tolerance. By maintaining copies of the database on multiple servers, a system can continue operating even if one server goes down. This can be done through synchronous or asynchronous replication, where changes are mirrored in real-time or slightly delayed, respectively. For example, if the primary database server fails, a standby server can take over, ensuring that users can still access the database without significant interruption. These combined strategies help relational databases maintain high availability and protect against data loss, making them a reliable choice for mission-critical applications.