How are transactions managed in relational databases?

Transactions in relational databases are managed through mechanisms that ensure data integrity and reliability, even when multiple operations occur simultaneously. A transaction is a sequence of database operations (like inserts, updates, or deletes) treated as a single logical unit. To maintain correctness, databases follow the ACID properties: Atomicity (all operations succeed or fail together), Consistency (the database remains in a valid state), Isolation (transactions don’t interfere with each other), and Durability (completed transactions survive system failures). For example, transferring money between bank accounts requires deducting from one account and crediting another—both steps must succeed, or neither should apply.

Databases manage transactions using transaction control statements like BEGIN, COMMIT, and ROLLBACK. When a transaction starts, the database tracks changes in a temporary state until the user commits. If an error occurs, the transaction rolls back, undoing all changes. For durability, databases use write-ahead logging (WAL), where changes are recorded to a log file before being applied to the actual data. This ensures recovery after crashes. For example, if a power failure happens mid-transaction, the database can replay the log to restore committed changes. Isolation is handled via locking (preventing concurrent access to data) or multi-version concurrency control (MVCC), which allows non-blocking reads by maintaining multiple versions of data.

Developers can influence transaction behavior through isolation levels like READ COMMITTED or SERIALIZABLE. Lower isolation levels (e.g., READ UNCOMMITTED) improve performance but risk inconsistencies like dirty reads. Higher levels (e.g., SERIALIZABLE) prevent anomalies but may cause contention. For instance, an e-commerce system might use REPEATABLE READ to ensure inventory counts stay consistent during checkout. Deadlocks—where transactions wait indefinitely for each other’s locks—are resolved by aborting one transaction. Tools like SAVEPOINT allow partial rollbacks within a transaction, enabling finer control. By combining these features, relational databases balance reliability, performance, and scalability for real-world applications.