How Pessimistic Locking works in PostgreSQL?

Pessimistic locking in PostgreSQL is implemented using explicit lock commands, allowing transactions to explicitly acquire locks on specific database objects. These locks prevent other transactions from concurrently accessing or modifying the locked objects until the lock is released.

Here’s how pessimistic locking works in PostgreSQL:

1. Lock Types: PostgreSQL supports different types of locks, including row-level locks, table-level locks, and advisory locks. Row-level locks allow locking individual rows within a table, while table-level locks lock the entire table. Advisory locks are application-defined locks that can be used for synchronization purposes.

2. Lock Acquiring: To acquire a lock, a transaction can use the LOCK command or the SELECT ... FOR UPDATE statement. The LOCK command allows locking specific tables or rows, while SELECT ... FOR UPDATE locks selected rows within a transaction. These commands can specify the lock mode, such as exclusive lock or shared lock, depending on the desired level of concurrency.

3. Lock Conflict Resolution: If a transaction tries to acquire a lock on an object that is already locked by another transaction, PostgreSQL follows a predefined set of rules to handle lock conflicts. The transaction requesting the lock may wait until the lock is released or may be canceled or blocked, depending on the lock mode and the configuration of the database.

4. Lock Release: Locks acquired by a transaction are automatically released when the transaction is committed or rolled back. However, it is also possible to release locks explicitly using the UNLOCK command.

Pessimistic locking is typically used in situations where data consistency is critical, and conflicts need to be avoided. However, it can also lead to reduced concurrency and potential performance issues if locks are held for a long time, causing blocking of other transactions.

It’s important to note that PostgreSQL also provides an alternative approach called Multiversion Concurrency Control (MVCC), which is the default concurrency control mechanism. MVCC uses optimistic locking by allowing concurrent transactions to operate on the same data without blocking each other, thereby maximizing concurrency while ensuring data consistency.

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About Shiv Iyer 330 Articles
Open Source Database Systems Engineer with a deep understanding of Optimizer Internals, Performance Engineering, Scalability and Data SRE. Shiv currently is the Founder, Investor, Board Member and CEO of multiple Database Systems Infrastructure Operations companies in the Transaction Processing Computing and ColumnStores ecosystem. He is also a frequent speaker in open source software conferences globally.