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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 ).
One of the architecture techniques is the split between managing transaction data and (master) reference data. Another is splitting data capture systems from data retrieval systems (as done in a data warehouse). Technology drivers These are usually suggested by the completed data architecture and database architecture designs.
The nested set model is a technique for representing nested set collections (also known as trees or hierarchies) in relational databases.. It is based on Nested Intervals, that "are immune to hierarchy reorganization problem, and allow answering ancestor path hierarchical queries algorithmically — without accessing the stored hierarchy relation".
An example of a database abstraction layer on the language level would be ODBC that is a platform-independent implementation of a database abstraction layer. The user installs specific driver software , through which ODBC can communicate with a database or set of databases.
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 .
The name is commonly used when creating a query to the database. The Database Source Name (DSN) does not have to be the same as the filename for the database. For example, a database file named "friends.mdb" could be set up with a DSN of "school". Then DSN "school" would then be used to refer to the database when performing a query.
Time taken to access any record is the same because the same number of nodes is searched; Index is a full index so data file does not have to be ordered; Pros and cons versatile data structure – sequential as well as random access; access is fast; supports exact, range, part key and pattern matches efficiently.
Database design is the organization of data according to a database model. The designer determines what data must be stored and how the data elements interrelate. With this information, they can begin to fit the data to the database model. [1] A database management system manages the data accordingly.