Codd's twelve rules [1] are a set of thirteen rules (numbered zero to twelve) proposed by Edgar F. Codd, a pioneer of the relational model for databases, designed to define what is required from a database management system in order for it to be considered relational, i.e., a relational database management system (RDBMS). [2] [3] They are sometimes referred to as "Codd's Twelve Commandments". [4]
Codd originally set out the rules in 1970, and developed them further in a 1974 conference paper. [5] His aim was to prevent the vision of the original relational database from being diluted, as database vendors scrambled in the early 1980s to repackage existing products with a relational veneer.[ citation needed ] Rule 12 was particularly designed to counter such a positioning.[ citation needed ]
While in 1999, a textbook stated "Nowadays, most RDBMSs ... pass the test". [5] another in 2007 suggested "no database system complies with all twelve rules." [6] Codd himself, in his book "The Relational Model for Database Management: Version 2", acknowledged that while his original set of 12 rules can be used for coarse distinctions, the 333 features of his Relational Model Version 2 (RM/V2) are needed for distinctions of a finer grain. [7]
Rule 0: The foundation rule:
Rule 1: The information rule:
Rule 2: The guaranteed access rule:
Rule 3:Systematic treatment of null values:
Rule 4:Dynamic online catalog based on the relational model:
Rule 5: The comprehensive data sublanguage rule:
Rule 6: The view updating rule:
Rule 7: Relational Operations Rule / Possible for high-level insert, update, and delete:
Rule 8:Physical data independence:
Rule 9:Logical data independence:
Rule 10:Integrity independence:
Rule 11:Distribution independence:
Rule 12: The nonsubversion rule:
In computing, a database is an organized collection of data stored and accessed electronically. Small databases can be stored on a file system, while large databases are hosted on computer clusters or cloud storage. The design of databases spans formal techniques and practical considerations, including data modeling, efficient data representation and storage, query languages, security and privacy of sensitive data, and distributed computing issues, including supporting concurrent access and fault tolerance.
Database normalization or database normalisation is the process of structuring a relational database in accordance with a series of so-called normal forms in order to reduce data redundancy and improve data integrity. It was first proposed by British computer scientist Edgar F. Codd as part of his relational model.
A relational database is a database based on the relational model of data, as proposed by E. F. Codd in 1970. A system used to maintain relational databases is a relational database management system (RDBMS). Many relational database systems are equipped with the option of using SQL for querying and updating the database.
The relational model (RM) is an approach to managing data using a structure and language consistent with first-order predicate logic, first described in 1969 by English computer scientist Edgar F. Codd, where all data is represented in terms of tuples, grouped into relations. A database organized in terms of the relational model is a relational database.
Structured Query Language (SQL), is a domain-specific language used in programming and designed for managing data held in a relational database management system (RDBMS), or for stream processing in a relational data stream management system (RDSMS). It is particularly useful in handling structured data, i.e. data incorporating relations among entities and variables.
Data integrity is the maintenance of, and the assurance of, data accuracy and consistency over its entire life-cycle and is a critical aspect to the design, implementation, and usage of any system that stores, processes, or retrieves data. The term is broad in scope and may have widely different meanings depending on the specific context – even under the same general umbrella of computing. It is at times used as a proxy term for data quality, while data validation is a prerequisite for data integrity. Data integrity is the opposite of data corruption. The overall intent of any data integrity technique is the same: ensure data is recorded exactly as intended. Moreover, upon later retrieval, ensure the data is the same as when it was originally recorded. In short, data integrity aims to prevent unintentional changes to information. Data integrity is not to be confused with data security, the discipline of protecting data from unauthorized parties.
A data model is an abstract model that organizes elements of data and standardizes how they relate to one another and to the properties of real-world entities. For instance, a data model may specify that the data element representing a car be composed of a number of other elements which, in turn, represent the color and size of the car and define its owner.
Edgar Frank "Ted" Codd was an English computer scientist who, while working for IBM, invented the relational model for database management, the theoretical basis for relational databases and relational database management systems. He made other valuable contributions to computer science, but the relational model, a very influential general theory of data management, remains his most mentioned, analyzed and celebrated achievement.
First normal form (1NF) is a property of a relation in a relational database. A relation is in first normal form if and only if no attribute domain has relations as elements. Or more informally, that no table column can have tables as values. Database normalization is the process of representing a database in terms of relations in standard normal forms, where first normal is a minimal requirement. SQL-92 does not support creating or using table-valued columns, which means that using only the "traditional relational database features" most relational databases will be in first normal form by necessity. Database systems which do not require first normal form are often called NoSQL systems. Newer SQL standards like SQL:1999 have started to allow so called non-atomic types, which include composite types. Even newer versions like SQL:2016 allow JSON.
The database schema is the structure of a database described in a formal language supported by the database management system (DBMS). The term "schema" refers to the organization of data as a blueprint of how the database is constructed. The formal definition of a database schema is a set of formulas (sentences) called integrity constraints imposed on a database. These integrity constraints ensure compatibility between parts of the schema. All constraints are expressible in the same language. A database can be considered a structure in realization of the database language. The states of a created conceptual schema are transformed into an explicit mapping, the database schema. This describes how real-world entities are modeled in the database.
Referential integrity is a property of data stating that all its references are valid. In the context of relational databases, it requires that if a value of one attribute (column) of a relation (table) references a value of another attribute, then the referenced value must exist.
A sublanguage is a subset of a language. Sublanguages occur in natural language, computer programming language, and relational databases.
Dataphor is an open-source truly-relational database management system (RDBMS) and its accompanying user interface technologies, which together are designed to provide highly declarative software application development. The Dataphor Server has its own storage engine or it can be a virtual, or federated, DBMS, meaning that it can utilize other database engines for storage.
In SQL, null or NULL is a special marker used to indicate that a data value does not exist in the database. Introduced by the creator of the relational database model, E. F. Codd, SQL null serves to fulfil the requirement that all true relational database management systems (RDBMS) support a representation of "missing information and inapplicable information". Codd also introduced the use of the lowercase Greek omega (ω) symbol to represent null in database theory. In SQL, NULL
is a reserved word used to identify this marker.
The object–relational impedance mismatch is a set of conceptual and technical difficulties that are often encountered when a relational database management system (RDBMS) is being served by an application program written in an object-oriented programming language or style, particularly because objects or class definitions, must be mapped to database tables defined by a relational schema.
Integration DEFinition for information modeling (IDEF1X) is a data modeling language for the development of semantic data models. IDEF1X is used to produce a graphical information model which represents the structure and semantics of information within an environment or system.
The Alpha language was the original database language proposed by Edgar F. Codd, the inventor of the relational database approach. It was defined in Codd's 1971 paper "A Data Base Sublanguage Founded on the Relational Calculus". Alpha influenced the design of QUEL. It was eventually supplanted by SQL, which IBM developed for its first commercial relational database product.
A database model is a type of data model that determines the logical structure of a database. It fundamentally determines in which manner data can be stored, organized and manipulated. The most popular example of a database model is the relational model, which uses a table-based format.
Codd's theorem states that relational algebra and the domain-independent relational calculus queries, two well-known foundational query languages for the relational model, are precisely equivalent in expressive power. That is, a database query can be formulated in one language if and only if it can be expressed in the other.
The following is provided as an overview of and topical guide to databases: