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an overall enterprise architecture that favors shared data models [5] over allowing each application to have its own, idiosyncratic data model. Even an extreme database-centric architecture called RDBMS-only architecture [6] [7] has been proposed, in which the three classic layers of an application are kept within the RDBMS. This architecture ...
[1] [2] Data redundancy can also be used as a measure against silent data corruption; for example, file systems such as Btrfs and ZFS use data and metadata checksumming in combination with copies of stored data to detect silent data corruption and repair its effects. [3]
Database normalization 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 .
Data independence is the type of data transparency that matters for a centralized DBMS. [1] It refers to the immunity of user applications to changes made in the definition and organization of data. Application programs should not, ideally, be exposed to details of data representation and storage.
The database schema is the structure of a database described in a formal language supported typically by a relational database management system (RDBMS). The term " schema " refers to the organization of data as a blueprint of how the database is constructed (divided into database tables in the case of relational databases ).
The internal structure of the database should be unaffected by changes to the physical aspects of the storage: For example, a changeover to a new disk. The three levels are: External Level (User Views): A user's view of the database describes a part of the database that is relevant to a particular user. It excludes irrelevant data as well as ...
By contrast, column-oriented DBMS store all data from a given column together in order to more quickly serve data warehouse-style queries. Correlation databases are similar to row-based databases, but apply a layer of indirection to map multiple instances of the same value to the same numerical identifier.
Data replication and computation replication both require processes to handle incoming events. Processes for data replication are passive and operate only to maintain the stored data, reply to read requests and apply updates. Computation replication is usually performed to provide fault-tolerance, and take over an operation if one component fails.