Distributed databases manage failures through a combination of redundancy, data replication, and consensus protocols. When a part of a database fails, the remaining nodes in the distributed system can continue to function without losing data or availability. This is typically achieved by maintaining multiple copies of the data across different nodes. For instance, if a node goes offline, another node that holds a replica can serve the requests, ensuring users experience minimal disruption.
Most distributed databases employ techniques like two-phase commit or Paxos to ensure that changes to the database state are consistently applied, even in the face of failures. In a transaction involving multiple nodes, the two-phase commit protocol ensures that either all nodes commit the transaction or none do, preventing partial updates that could lead to data inconsistency. Similarly, consensus protocols help nodes agree on a single value, which is crucial when nodes experience different failures. For example, Apache Cassandra uses a protocol called Gossip to share information about node availability and state, allowing it to automatically detect and handle failed nodes.
Another fundamental aspect is the ability to perform automatic failover. When a node fails, the system can automatically switch to another node that has the required data or services. For example, if a master node in a primary-replica setup fails, the system can promote a replica to become the new master. This automatic recovery minimizes downtime and keeps the application running smoothly. Overall, by using redundancy, consensus mechanisms, and automatic failover processes, distributed databases can handle failures effectively and maintain high availability and data integrity.