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Aphysical data model (ordatabase design) is a representation of a data design as implemented, or intended to be implemented, in adatabase management system. In thelifecycle of a project it typically derives from alogical data model,[2] though it may bereverse-engineered from a givendatabase implementation. A complete physical data model will include all thedatabase artifacts required to createrelationships between tables or to achieve performance goals, such asindexes, constraint definitions,linking tables,partitioned tables orclusters. Analysts can usually use a physical data model to calculate storage estimates; it may include specific storage allocation details for a given database system.
As of 2012[update] seven main databases dominate the commercial marketplace:Informix,Oracle,Postgres,SQL Server,Sybase,IBM Db2 andMySQL. Other RDBMS systems tend either to be legacy databases or used within academia such as universities or further education colleges. Physical data models for each implementation would differ significantly, not least due to underlyingoperating-system requirements that may sit underneath them. For example:SQL Server runs only onMicrosoft Windows operating-systems (Starting with SQL Server 2017, SQL Server runs on Linux. It's the same SQL Server database engine, with many similar features and services regardless of your operating system[3]), while Oracle and MySQL can run on Solaris, Linux and other UNIX-based operating-systems as well as on Windows. This means that the disk requirements, security requirements and many other aspects of a physical data model will be influenced by the RDBMS that adatabase administrator (or an organization) chooses to use.
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Physical schema is a term used indata management to describe howdata is to be represented and stored (files, indices, etc.) insecondary storage using a particulardatabase management system (DBMS) (e.g.,Oracle RDBMS, Sybase SQL Server, etc.).
In theANSI/SPARC Architecturethree schema approach, theinternal schema is the view of data that involved data management technology. This is as opposed to anexternal schema that reflects an individual's view of the data, or theconceptual schema that is the integration of a set of external schemas.
Subsequently,[4] the internal schema was recognized to have two parts:
Thelogical schema was the way data were represented to conform to the constraints of a particular approach to database management. At that time the choices werehierarchical andnetwork. Describing the logical schema, however, still did not describe how physically data would be stored on disk drives. That is the domain of thephysical schema. Now logical schemas describe data in terms of relationaltables and columns, object-orientedclasses, andXMLtags.[5]
A single set of tables, for example, can be implemented in numerous ways, up to and including an architecture where table rows are maintained on computers in different countries.