What is the difference between a trigger and a constraint in SQL?

Triggers can be defined at different level 1. Database level. Eg. AFTER DDL ON DATABASE 2. Schema/User Level. Eg. ON LOGON 3. Object Level DML triggers. Eg. INSERT, UPDATE, DELETE. Trigger can be further divided into BEFORE and AFTER i.e. whether it would execute befor or after the defined event. Object Level DML triggers can be further classified into ROW level or STATEMENT level, means only once for the entire statement irrespective of number of records it is affecting or once for each row. Trigger is block of code where we can write any valid procedural statement. It has few additional functions using which we can access OLD and NEW values. DML triggers are always part of main transaction. ROLLBACK/COMMIT actions are done at main txn

We have all played Mario Bros. video game. In the game when Mario collects a star, it triggers a super power in the character! Similarly, triggers are a set of instructions that watches for a certain event to happen and in turn forces database to "automatically" do something in response.. It can be an insert in the table or a delete from a table and these events can trigger other events. For example, in an online store, one can setup a trigger to subtract the inventory by 1 , anytime a purchase is made. In another example, let's say in a university database, if the grades of a student are adjusted, then the "last modified date" column can automatically be updated using a trigger.

In SQL, a trigger is a set of instructions or procedures that are automatically executed, or "triggered," in response to certain events on a particular table or view. These events include data manipulation language (DML) events such as INSERT, UPDATE, DELETE operations, and sometimes data definition language (DDL) events like CREATE, ALTER, or DROP. Triggers are often used to enforce referential integrity, perform logging, or automate complex business rules that involve multiple tables. They are defined to execute in response to a specific event and are associated with a particular table or view.

Constraints: Constraints are predefined rules applied to tables, ensuring data accuracy and consistency. They enforce specific conditions on columns, preserving data integrity by limiting acceptable values or relationships. Triggers: Triggers are automatic actions triggered by specific database events (e.g., INSERT, UPDATE, DELETE). They execute code or procedures in response to these events, allowing dynamic responses or additional operations. Triggers are used for complex logic, auditing changes, or enforcing specific behaviors after data manipulation.

Though the trigger has many use cases, it is often overlooked, when investigating a problem. Oftentimes, it is the last thing to be checked in the chain of possible causes, and its "hidden" nature flushes it out of plain sight. Therefore, it is important to be well documented, and its role in the whole - well understood.

It is a validation rule. 1. Check for uniqueness. 2. Validation on the basis of list of values. 3. Validation of range of values. 4. Validation of NOT NULL. 5. Validation of referential integrity constraint. 6. To some extent logical validation of the rule is also possible by making combination of CASE statement along with UNIQUE check.

A constraint is like a rule that keeps your data well-behaved. For example, think of a foreign key constraint as ensuring that if you mention a friend in one part of your data, that friend actually exists in another part. Constraints help maintain the reliability and structure of your data, much like rules in a game or guidelines for organizing information.

2 types de contraintes Les relationnelles : un atout pour valider automatiquement la cohérence des relations de données entre les tables (cf. Merise) un atout sur un jeu de données statiques, non mouvant, à contrario sur des tables volumineuses car chaque enregistrement sera checké unitairement, cependant il existe l'option de les activer ou désactiver de fa?on dynamique. Les contraintes "check" Permet de valider les valeurs unitaires de chaque colonne et garantir la cohérence de données. Très conseillée d'autant plus si les flux d'interfaces entrantes sont ma?trisés

A constraint prevents you (or an action) from doing something. For example, if you attempt to add a duplicate record, then this would be a constraint and it would prevent you from adding it. Or for example, it could be that you are only allowed to enter dates in a certain range, that is a constraint.

Constraints and Triggers both are different things in a database. Constraint is used on a single table whereas Trigger is used on multiple tables. For every table creation, we need to use constraints but sometimes we need to use triggers for our complex logic. Constraints are easier to handle than Triggers. By imposing constraints, we can prevent duplicate data entry.

Constraints are more like rules that a table has to follow. Triggers are special events that happen in response to a certain event. Imagine in a game of soccer, you can only use your hands unless you're a goalkeeper. And a penalty kick is a trigger that happens in response to an event if another player commits foul inside their own penalty area. Here are some of the differences: 1. Constrains only apply to the data within a single table. Triggers can modify multiple tables. 2. Constraints are more simpler while triggers can contain more complex logic. Since constraints are simpler, they are more faster.

Think of a trigger like a surprise party, it's an action (event) that automatically leads to a response (the party). In SQL, a trigger responds to events like inserting, updating, or deleting data. On the other hand, a constraint is like a rule in a game. Imagine a rule that says, "You can't use your hands." This rule (constraint) ensures that players follow a specific behavior to maintain the integrity of the game, just like how SQL constraints maintain data integrity in a database.

One difference - Constraints are proactive ,triggers reactive , for example - check constraint prevent inserting data in table which do not comply with rules if we want to achieve this with trigger we first will insert data and then rollback this if inserted data not comply - performance is slower

Constraints are basic rules you define that limit (constrain) the type or values of data entered into specific database table field column(s). Constraints are used to ensure basic data integrity. Triggers are procedures (customized logic) that are designed to execute Before or After specific SQL operations are executed such a INSERT, UPDATE, DELETE on specific tables. They allow a developer to use more complex/customized logic in response to operational events. Triggers go above and beyond basic data restrictions/limits that constraints offer. Triggers are most useful when architecting database event driven design patterns, based upon specific types of operations on specific tables. There's a wide range of things which can be done.

Très bon exemple auquel il manquerait la gestion d'erreur et éventuellement de commit/rollback pour être complet cf. ma contribution d'usage sur la définition du déclencheur

Constraints in SQL define rules for data integrity (e.g., foreign keys, unique values) at the table level, preventing invalid data entry. Triggers, however, are specialized procedures that automatically execute in response to specific data modification events (e.g., INSERT, UPDATE, DELETE). While constraints immediately enforce rules during data operations, triggers perform actions or enforce rules based on events and can involve more complex operations across tables. Constraints are static, defined with table creation or modification, while triggers are separate objects that respond to events after they occur.

Triggers can be very powerful, but care must be taken when developing them. If a strong understanding of the processes that trigger them is not in place, it can lead to slowness or even deadlocks.

Incorporating constraints and triggers into a database schema goes beyond mere data validity—it's about embodying the business logic at the data layer, ensuring consistency, and maintaining the integrity of the database even in the face of complex and unforeseen interactions. One particular application of triggers I've employed was to create a history table that automatically archives previous states of a record upon update. This not only served as an audit trail but also allowed us to quickly restore data to a prior state in case of erroneous updates, which can be a common occurrence in dynamic production environments. When used judiciously, triggers can serve as a critical component in preserving the evolution of your data over time.

In the context of SQL Server Triggers, there are two "special tables" known as inserted and deleted. Let's say we have an Employee table and in a new year , the salary of an employee is updated. On the Employee table, we also have a trigger that maintains an audit history of the employee. In such cases, special tables like inserted and deleted would hold the new and old salary of the employee. Example: Create Trigger updateTrigger on dbo.employee for update as begin declare @empID int select @empID = i.id from inserted i declare @oldSalary long, @newsalary long select @oldSalary = d.salary from deleted d select @newSalary = i.salary from inserted i Insert into EmployeeAudit values(@empID, @oldSalary, @newSalary, getdate()) End;

Triggers are exceptionally powerful, when combined with SP's (Stored Procedure's), Extended SP's and more. The features available to tap into vary between database systems. Useful for Business Logic, database integrity, and even being able to signal or Message queue other services and (insert wide range of possibilities). I've incorporated queue systems for the creation/generation of static web content when database content was updated. A real time saver to automat all kinds of processes and logic. Anything that is connected with changes on the data layer. I've even designed mini Datawarehouse systems for smaller applications. This is a must learn facet of databases.

A prendre en compte : Fréquence des traitements Volume initial de data et projeté Usage final : exemple en opposé (lourd) décisionnel, inventaire à (light) gestion de client, d'article via un écran de saisie