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Database History PowerPoint PPT Presentation

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Database History. 1960s Legacy Systems: Hierarchical and Network DBMS 1970s Relational DBMS 1980s Non conventional DBMS. Non conventional DBMS (OO, Object Relational, Deductive, etc.) .

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Database History

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Database history l.jpg

Database History

  • 1960s Legacy Systems: Hierarchical and Network DBMS

  • 1970s Relational DBMS

  • 1980s Non conventional DBMS

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Non conventional DBMS(OO, Object Relational, Deductive, etc.)

Relational Database works well to store just text and numbers as long as there are not many multi-valued attributes.

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Advantages of ORDBMS,OODBMS

  • Multi-valued attributes,

  • Super/Sub-types: inheritance

  • Interfaces well with OOPL

  • Multi-media

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Serve many applications

Integrity constraints




Easy query language

Permanent Objects

Classes and Objects

Properties and Methods

Events and Messages



Multiple Inheritance and Polymorphism


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Characteristics of OODBMS

  • Not as standard as Relational DBMS

  • Object ID (system unique, immutable, not visible by end-user)

  • Versions

  • Many different types of records as opposed to Relational DBMS (many instances of few different types of records)

  • Spatial Component

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Common OO Applications

  • Computer-aided design (CAD)

  • Computer-aided manufacturing (CAM)

  • Geographic information systems (GIS)

  • Office Automation

  • Computer-aided publishing

  • Multimedia databases

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Non Conventional DBMS

  • Object Relational (Extend the Relational Model)

  • Construct an OODBMS from scratch

  • Knowledge Base Management Systems (OODBMS).

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Object Relational

  • Examples:

    Informix Universal Server (many OO features)


    MS-Access (very limited, picture field)

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Informix Universal Server-History

  • INGRES (Relational DBMS – UC Berkeley)

  • POSTGRES (OO features added to INGRES at UC Berkeley)

  • Montage -> Miro -> Ilustra

  • Ilustra + Informix (relational DBMS that dominated market in 80s with Sybase & Oracle).

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Datatypes in Informix US

  • Two dimensional data type (line circle, polygon, path)

  • Image data types: supports TIFF, GIF, JPEG, photoCD, GROUP 4 and Fax.

  • Time series data type

  • Opaque, Distinct, Row type and Collection Type

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  • Multivalued attributes using VARRAY

  • Object type

  • BLOB (Binary large object), CLOB (Characters), BFILE (Binary File), NCLOG (Intern. Characters)

  • 9i: Inheritance

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OODBMS references (products)

  • O2

  • Gemstone

  • Objectstore


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ORDBMS examples

  • Points, Lines and Circles

  • ASU: University DB Example

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Knowledge Base/Deductive DB

  • Expert System + Database Technology

  • Stores rules instead of data

  • Basically Prototypes available at Universities and Research Institutions

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Examples of Knowledge BaseDBMS

Datalog (combines PROLOG + Database technology).


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GIS Life Expectancy

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GIS Population

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