---
title: "PostgreSQL Locking and Concurrency Control"
description: "An in-depth guide to PostgreSQL's locking mechanisms and concurrency control features"
keywords: ["postgresql", "locking", "concurrency", "transactions", "isolation"]
category: "databases"
---

PostgreSQL provides a range of locking modes to manage concurrent access to data. The most common lock modes are ACCESS SHARE, ROW SHARE, ROW EXCLUSIVE, SHARE UPDATE EXCLUSIVE, SHARE, SHARE ROW EXCLUSIVE, and ACCESS EXCLUSIVE. ACCESS SHARE locks are held by SELECT statements and prevent the table from being dropped or altered. ROW SHARE locks are acquired when a row is selected for update, while ROW EXCLUSIVE locks are obtained when a row is being modified. SHARE UPDATE EXCLUSIVE locks are used for VACUUM operations. SHARE locks prevent concurrent writes but allow reads, and SHARE ROW EXCLUSIVE locks prevent concurrent writes and only allow reads. Finally, ACCESS EXCLUSIVE locks are the strongest, preventing any other operations on the table while held.

In addition to these built-in lock modes, PostgreSQL also supports advisory locks, which are application-defined locks that can be used to coordinate access to shared resources outside the database. Advisory locks are acquired and released using the pg_advisory_lock() and pg_advisory_unlock() functions, and can be used to implement application-level concurrency control mechanisms.

PostgreSQL provides automatic deadlock detection to identify and resolve deadlock situations. When a deadlock is detected, one of the transactions involved is chosen as the deadlock victim and is rolled back, with the ERROR 40P01: deadlock detected message being returned. To aid in debugging deadlocks, the log_lock_waits configuration parameter can be enabled to log information about lock wait events.

Postgres also supports lock timeouts, which can be configured using the statement_timeout and lock_timeout parameters. The statement_timeout setting specifies the maximum duration for a SQL statement, while the lock_timeout setting determines the maximum time a transaction will wait to acquire a lock before giving up.

PostgreSQL's locking system operates at both the row level and the table level. Row-level locks are acquired when individual rows are accessed, while table-level locks are obtained when an entire table is accessed. The level of locking used depends on the type of operation being performed and the isolation level of the transaction.

Postgres implements Multiversion Concurrency Control (MVCC) to provide snapshot isolation for transactions. Each transaction sees a consistent view of the data as it existed at the time the transaction began, even if other transactions have modified the data since then. This allows for highly concurrent access to the database without the need for explicit locking in many cases.

For applications that require stronger isolation guarantees, PostgreSQL supports serializable transactions, which use predicate locks to ensure that the outcome of a set of concurrent transactions is the same as if they had been executed in a serial order. Predicate locks are acquired on the predicates (WHERE clauses) used in SELECT statements, preventing other transactions from modifying data that would affect the result set.Continuing the comprehensive technical documentation on PostgreSQL Locking and Concurrency Control:

PostgreSQL's MVCC implementation is further enhanced by the use of a visibility map, which tracks which pages in the database contain only committed tuples. This allows the database to quickly determine which pages can be scanned without the need to check individual row visibility, improving query performance. The visibility map is maintained automatically by the database, with updates occurring during INSERT, UPDATE, DELETE, and VACUUM operations.

Alongside MVCC, PostgreSQL also supports the use of serializable transactions, which provide the strongest isolation level available. Serializable transactions use predicate locks to ensure that the outcome of a set of concurrent transactions is equivalent to a serial execution of those transactions. Predicate locks are acquired on the predicates (WHERE clauses) used in SELECT statements, preventing other transactions from modifying data that would affect the result set.

The SERIALIZABLE isolation level can be enabled at the transaction level using the SET TRANSACTION ISOLATION LEVEL SERIALIZABLE command, or as the default for a session using the default_transaction_isolation configuration parameter. When a serializable conflict is detected, PostgreSQL will raise the ERROR 40001: could not serialize access due to concurrent update error, allowing the application to handle the conflict and retry the transaction if necessary.

In addition to the built-in lock modes and isolation levels, PostgreSQL also provides a set of advisory lock functions that allow applications to define and manage their own custom lock types. The pg_advisory_lock() and pg_advisory_unlock() functions can be used to acquire and release these application-defined locks, which can be useful for coordinating access to shared resources outside the database, such as distributed systems or external services.

The performance impact of PostgreSQL's locking and concurrency control mechanisms can be monitored and analyzed using various system views and functions. The pg_locks system view provides information about all the locks currently held in the database, including the type of lock, the object being locked, and the transaction holding the lock. The pg_stat_activity view can also be used to track lock wait times and identify transactions that are experiencing lock contention.Continuing the comprehensive technical documentation on PostgreSQL Locking and Concurrency Control:

To help diagnose and resolve lock-related issues, PostgreSQL provides the log_lock_waits configuration parameter, which can be enabled to log information about lock wait events. When log_lock_waits is set to on, the database will log a message whenever a transaction has to wait more than the specified log_lock_waits_timeout (default is 1 second) to acquire a lock. This can be a valuable tool for identifying long-running lock contention and potential deadlock situations.

In addition to the standard lock modes, PostgreSQL also supports the use of advisory locks, which are application-defined locks that can be used to coordinate access to shared resources outside the database. Advisory locks are acquired and released using the pg_advisory_lock() and pg_advisory_unlock() functions, and can be useful for implementing application-level concurrency control mechanisms, such as distributed locking or resource allocation.

PostgreSQL's locking and concurrency control features are designed to provide a high degree of data consistency and availability, while also allowing for a high degree of concurrency. By leveraging MVCC and serializable transactions, the database can support a large number of concurrent users and workloads, with automatic deadlock detection and resolution to ensure data integrity.

Overall, PostgreSQL's locking and concurrency control mechanisms are a crucial aspect of the database's functionality, providing a robust and flexible framework for managing concurrent access to data. By understanding the various lock modes, isolation levels, and monitoring tools available, database administrators and application developers can ensure that their PostgreSQL-based systems are able to handle high levels of concurrent activity while maintaining data consistency and integrity.Continuing the comprehensive technical documentation on PostgreSQL Locking and Concurrency Control:

One of the key features of PostgreSQL's concurrency control system is its support for serializable transactions, which provide the highest level of isolation available. Serializable transactions use predicate locks to ensure that the outcome of a set of concurrent transactions is equivalent to a serial execution of those transactions. Predicate locks are acquired on the predicates (WHERE clauses) used in SELECT statements, preventing other transactions from modifying data that would affect the result set.

The SERIALIZABLE isolation level can be enabled at the transaction level using the SET TRANSACTION ISOLATION LEVEL SERIALIZABLE command, or as the default for a session using the default_transaction_isolation configuration parameter. When a serializable conflict is detected, PostgreSQL will raise the ERROR 40001: could not serialize access due to concurrent update error, allowing the application to handle the conflict and retry the transaction if necessary.

Serializable transactions in PostgreSQL are implemented using a technique called Serializable Snapshot Isolation (SSI), which extends the basic MVCC model to provide stronger guarantees about the consistency of query results. SSI works by tracking the read and write sets of each transaction and using predicate locks to detect potential conflicts between concurrent transactions.

In addition to the built-in lock modes and isolation levels, PostgreSQL also provides a set of advisory lock functions that allow applications to define and manage their own custom lock types. The pg_advisory_lock() and pg_advisory_unlock() functions can be used to acquire and release these application-defined locks, which can be useful for coordinating access to shared resources outside the database, such as distributed systems or external services.

The performance impact of PostgreSQL's locking and concurrency control mechanisms can be monitored and analyzed using various system views and functions. The pg_locks system view provides information about all the locks currently held in the database, including the type of lock, the object being locked, and the transaction holding the lock. The pg_stat_activity view can also be used to track lock wait times and identify transactions that are experiencing lock contention.