How do relational databases ensure fault tolerance?

Relational databases ensure fault tolerance through replication, transaction logging, and automated failover mechanisms. By maintaining copies of data across multiple servers, they prevent single points of failure. For example, a primary-replica setup allows a standby server to take over if the primary fails. Replication can be synchronous (ensuring zero data loss but with latency trade-offs) or asynchronous (prioritizing performance with minimal downtime). Tools like PostgreSQL’s streaming replication or MySQL’s group replication automate this process, enabling seamless transitions during outages. This redundancy ensures continuous availability even during hardware failures or network issues.

Transaction logging and ACID compliance (Atomicity, Consistency, Isolation, Durability) further enhance fault tolerance. Write-Ahead Logging (WAL) in databases like PostgreSQL records changes to a log file before applying them to the main database. If a crash occurs, the database uses this log to recover uncommitted transactions and restore consistency. The durability aspect of ACID guarantees that committed transactions survive system failures by persisting data to non-volatile storage. For instance, SQL Server’s transaction log allows point-in-time recovery, ensuring data integrity even after unexpected shutdowns or disk errors.

Backup strategies and storage redundancy also play critical roles. Regular full and incremental backups, combined with tools like pg_dump (PostgreSQL) or mysqldump (MySQL), enable recovery from catastrophic failures. Cloud-based databases often integrate automated backup solutions (e.g., AWS RDS snapshots). Storage redundancy via RAID configurations or distributed file systems (like AWS EBS) safeguards against disk failures. Additionally, clustered solutions such as SQL Server AlwaysOn Availability Groups or Oracle Real Application Clusters (RAC) distribute workloads and automatically reroute traffic during node failures. These layers of protection ensure minimal data loss and downtime in most failure scenarios.