How do you handle data synchronization and replication in distributed backend systems?
Data synchronization and replication are crucial aspects of managing data in distributed backend systems. When dealing with distributed systems, it is necessary to ensure that data remains consistent and up-to-date across multiple servers or nodes. Here are the key techniques and considerations involved in handling data synchronization and replication: Master-slave replication: Master-slave replication is a common approach where one node (the master) is considered the primary data source, and changes made on the master are replicated to one or more slave nodes. The slave nodes represent read-only copies of the data. The master is responsible for accepting write operations, while the slaves handle read operations. This approach provides fault tolerance, as read operations can still be performed even if the master node is unavailable. However, it introduces potential latency for read operations since they depend on the replication process. Multi-master replication: In multi-master replication, multiple nodes are designated as masters, and changes made on any master node are replicated to other