Relational databases handle distributed transactions through a coordinated approach that ensures data consistency across multiple database instances. When a transaction spans several databases, the system must maintain the integrity of the data even if some components fail. This is primarily managed by using a protocol called the Two-Phase Commit (2PC). In the first phase, the coordinator sends a request to all involved database nodes to prepare for the transaction. Each database responds with either a "vote commit" if it is ready to proceed or a "vote rollback" if it cannot. In the second phase, based on the votes, the coordinator instructs the databases to either commit or roll back the changes.
For instance, consider a banking application where a user transfers money from an account in one bank to another account in a different bank. The transaction involves two separate operations: debiting the sender's account and crediting the recipient's account. Using 2PC, the system ensures that both operations are treated as a single unit of work. If one bank cannot commit the transaction for some reason, such as a network interruption, the coordinator will signal both banks to roll back any changes, preventing any discrepancies between accounts.
In addition to 2PC, some systems use more advanced strategies like distributed consensus algorithms, such as Paxos or Raft, to manage transactions across multiple nodes. These approaches help in achieving stronger consistency models in scenarios where simultaneous transactions could lead to conflicts. Overall, while distributed transactions can be complex, employing these protocols allows relational databases to ensure that operations remain reliable and consistent across different locations.