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A check constraint is a type of integrity constraint in SQL which specifies a requirement that must be met by each row in a database table. The constraint must be a predicate . It can refer to a single column, or multiple columns of the table.
Let's set an example convention saying a book up to 350 pages is considered "slim" and a book over 350 pages is considered "thick". This convention is technically a constraint but it is neither a domain constraint nor a key constraint; therefore we cannot rely on domain constraints and key constraints to keep the data integrity.
SQL-92 was the third revision of the SQL database query language. Unlike SQL-89, it was a major revision of the standard. Aside from a few minor incompatibilities, the SQL-89 standard is forward-compatible with SQL-92. The standard specification itself grew about five times compared to SQL-89.
The formal definition of a database schema is a set of formulas (sentences) called integrity constraints imposed on a database. [citation needed] These integrity constraints ensure compatibility between parts of the schema. All constraints are expressible in the same language.
In database systems, consistency (or correctness) refers to the requirement that any given database transaction must change affected data only in allowed ways. Any data written to the database must be valid according to all defined rules, including constraints, cascades, triggers, and any combination thereof.
Example Left Right Narrative One-to-one: person ←→ birth certificate: 1: 1: A person must have their own birth certificate, it is specific to that person by its Id number. One-to-one (optional on one side) person ←→ driving license: 1: 0..1 or ? A person may have a driving license, it is specific to that person by its Id number. One-to-many
SQL was initially developed at IBM by Donald D. Chamberlin and Raymond F. Boyce after learning about the relational model from Edgar F. Codd [12] in the early 1970s. [13] This version, initially called SEQUEL (Structured English Query Language), was designed to manipulate and retrieve data stored in IBM's original quasirelational database management system, System R, which a group at IBM San ...
Data validation is intended to provide certain well-defined guarantees for fitness and consistency of data in an application or automated system. Data validation rules can be defined and designed using various methodologies, and be deployed in various contexts. [1]