A relational database handles concurrency by employing techniques that allow multiple users to access and manipulate data simultaneously without conflicts. At its core, concurrency control ensures that transactions are executed in a way that maintains the integrity of the database while allowing for efficient performance. Two primary methods for managing concurrency are locking mechanisms and optimistic concurrency control.
Locking mechanisms are commonly used to prevent conflicts when multiple transactions try to access the same data. When a transaction wants to modify a record, the database may place a lock on that record, preventing other transactions from modifying it until the first transaction is complete. There are different types of locks: exclusive locks prevent any other transaction from accessing the locked resource, while shared locks allow concurrent read access but prevent any modifications until the lock is released. For instance, if two users try to update the same customer record at the same time, the database will ensure that one update is completed before the other can proceed, maintaining data consistency.
On the other hand, optimistic concurrency control assumes that conflicts are rare and allows multiple transactions to proceed without locking resources initially. Instead of locking records, the database will check for conflicts only at the time of committing the transaction. If a conflict is detected—such as another transaction modifying the same data during the uptime—the system will typically roll back the transaction that tried to commit last or notify the user of the conflict. This approach can lead to better performance in scenarios with minimal contention, as it reduces the overhead associated with maintaining locks. Overall, these methods enable relational databases to effectively manage concurrent access while ensuring the reliability and correctness of transactions.