What is the ACID model and how does it relate to SQL databases?
Aug 02, 2025 am 10:51 AMACID ensures reliable database transactions in SQL databases through four key properties: 1. Atomicity guarantees that transactions are all-or-nothing—either all operations succeed or none do, preventing partial updates like in a bank transfer where both withdrawal and deposit must complete together; 2. Consistency ensures the database remains in a valid state before and after a transaction, adhering to all defined rules and constraints; 3. Isolation prevents interference between concurrent transactions, avoiding issues like dirty reads through mechanisms like locking or MVCC, with varying isolation levels balancing performance and safety; 4. Durability ensures that once a transaction is committed, its changes are permanently stored, even after system failures, typically via transaction logs. ACID is essential in SQL databases like PostgreSQL, MySQL (InnoDB), and Oracle for maintaining data integrity in critical applications such as banking and e-commerce, preventing data corruption, inconsistent reads, and data loss, thereby ensuring trustworthiness and reliability in transactional systems.
The ACID model is a set of properties that guarantee reliable processing of database transactions in SQL databases. It stands for Atomicity, Consistency, Isolation, and Durability. These principles ensure that database transactions are processed reliably, even in the event of system failures or concurrent access.

Here’s how each component works and why it matters in SQL databases:
1. Atomicity: All or Nothing
Atomicity ensures that a transaction is treated as a single, indivisible unit. Either all operations within the transaction are completed successfully, or none of them are applied.

- If any part of a transaction fails (e.g., due to a system crash or constraint violation), the entire transaction is rolled back.
- Example: When transferring money from one bank account to another, both the withdrawal and deposit must succeed. If one fails, the whole transaction is undone to prevent partial updates.
2. Consistency: Valid State Before and After
Consistency ensures that a transaction brings the database from one valid state to another, maintaining all defined rules (like constraints, triggers, and cascades).
- The database must not violate any integrity constraints during or after a transaction.
- This doesn’t mean the application logic is correct—just that the data remains in a structurally sound state according to the schema.
3. Isolation: Concurrent Transactions Don’t Interfere
Isolation ensures that concurrent transactions execute in a way that appears serial (one after another), even if they run at the same time.

- Prevents issues like dirty reads, non-repeatable reads, and phantom reads.
- SQL databases implement isolation through locking mechanisms or multi-version concurrency control (MVCC).
- Different isolation levels (e.g., Read Committed, Repeatable Read) allow trade-offs between performance and strictness.
4. Durability: Committed Data Survives Failures
Durability guarantees that once a transaction is committed, its changes are permanent—even if the system crashes immediately afterward.
- Achieved through writing transaction logs to persistent storage before acknowledging success.
- This ensures that committed data can be recovered during system restarts.
Why ACID Matters in SQL Databases
Relational databases (like PostgreSQL, MySQL with InnoDB, SQL Server, Oracle) are designed to support ACID compliance, especially for applications requiring data integrity—such as banking systems, inventory management, and e-commerce platforms.
Without ACID, you risk:
- Partial updates corrupting data
- Inconsistent reads during concurrent operations
- Loss of committed data after a crash
In short, ACID is foundational to how SQL databases maintain trustworthiness and reliability in transactional workloads. While some NoSQL databases sacrifice certain ACID properties for scalability, traditional SQL databases prioritize them to ensure data correctness.
Basically, if you're using SQL for critical operations, ACID is what lets you sleep at night.
The above is the detailed content of What is the ACID model and how does it relate to SQL databases?. For more information, please follow other related articles on the PHP Chinese website!

Hot AI Tools

Undress AI Tool
Undress images for free

Undresser.AI Undress
AI-powered app for creating realistic nude photos

AI Clothes Remover
Online AI tool for removing clothes from photos.

Clothoff.io
AI clothes remover

Video Face Swap
Swap faces in any video effortlessly with our completely free AI face swap tool!

Hot Article

Hot Tools

Notepad++7.3.1
Easy-to-use and free code editor

SublimeText3 Chinese version
Chinese version, very easy to use

Zend Studio 13.0.1
Powerful PHP integrated development environment

Dreamweaver CS6
Visual web development tools

SublimeText3 Mac version
God-level code editing software (SublimeText3)

Hot Topics

In database design, use the CREATETABLE statement to define table structures and constraints to ensure data integrity. 1. Each table needs to specify the field, data type and primary key, such as user_idINTPRIMARYKEY; 2. Add NOTNULL, UNIQUE, DEFAULT and other constraints to improve data consistency, such as emailVARCHAR(255)NOTNULLUNIQUE; 3. Use FOREIGNKEY to establish the relationship between tables, such as orders table references the primary key of the users table through user_id.

SQLfunctionsandstoredproceduresdifferinpurpose,returnbehavior,callingcontext,andsecurity.1.Functionsreturnasinglevalueortableandareusedforcomputationswithinqueries,whileproceduresperformcomplexoperationsanddatamodifications.2.Functionsmustreturnavalu

LAG and LEAD in SQL are window functions used to compare the current row with the previous row data. 1. LAG (column, offset, default) is used to obtain the data of the offset line before the current line. The default value is 1. If there is no previous line, the default is returned; 2. LEAD (column, offset, default) is used to obtain the subsequent line. They are often used in time series analysis, such as calculating sales changes, user behavior intervals, etc. For example, obtain the sales of the previous day through LAG (sales, 1, 0) and calculate the difference and growth rate; obtain the next visit time through LEAD (visit_date) and calculate the number of days between them in combination with DATEDIFF;

Pattern matching functions in SQL include LIKE operator and REGEXP regular expression matching. 1. The LIKE operator uses wildcards '%' and '_' to perform pattern matching at basic and specific locations. 2.REGEXP is used for more complex string matching, such as the extraction of email formats and log error messages. Pattern matching is very useful in data analysis and processing, but attention should be paid to query performance issues.

To find columns with specific names in SQL databases, it can be achieved through system information schema or the database comes with its own metadata table. 1. Use INFORMATION_SCHEMA.COLUMNS query is suitable for most SQL databases, such as MySQL, PostgreSQL and SQLServer, and matches through SELECTTABLE_NAME, COLUMN_NAME and combined with WHERECOLUMN_NAMELIKE or =; 2. Specific databases can query system tables or views, such as SQLServer uses sys.columns to combine sys.tables for JOIN query, PostgreSQL can be used through inf

Create a user using the CREATEUSER command, for example, MySQL: CREATEUSER'new_user'@'host'IDENTIFIEDBY'password'; PostgreSQL: CREATEUSERnew_userWITHPASSWORD'password'; 2. Grant permission to use the GRANT command, such as GRANTSELECTONdatabase_name.TO'new_user'@'host'; 3. Revoke permission to use the REVOKE command, such as REVOKEDELETEONdatabase_name.FROM'new_user

TheSQLLIKEoperatorisusedforpatternmatchinginSQLqueries,allowingsearchesforspecifiedpatternsincolumns.Ituseswildcardslike'%'forzeroormorecharactersand'_'forasinglecharacter.Here'showtouseiteffectively:1)UseLIKEwithwildcardstofindpatterns,e.g.,'J%'forn

Backing up and restoring SQL databases is a key operation to prevent data loss and system failure. 1. Use SSMS to visually back up the database, select complete and differential backup types and set a secure path; 2. Use T-SQL commands to achieve flexible backups, supporting automation and remote execution; 3. Recovering the database can be completed through SSMS or RESTOREDATABASE commands, and use WITHREPLACE and SINGLE_USER modes if necessary; 4. Pay attention to permission configuration, path access, avoid overwriting the production environment and verifying backup integrity. Mastering these methods can effectively ensure data security and business continuity.
