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Database History

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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  1. Database History • 1960s Legacy Systems: Hierarchical and Network DBMS • 1970s Relational DBMS • 1980s Non conventional DBMS

  2. 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.

  3. Advantages of ORDBMS,OODBMS • Multi-valued attributes, • Super/Sub-types: inheritance • Interfaces well with OOPL • Multi-media

  4. Serve many applications Integrity constraints Concurrency Security Views Easy query language Permanent Objects Classes and Objects Properties and Methods Events and Messages Inheritance Encapsulation Multiple Inheritance and Polymorphism DBMS + OO

  5. 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

  6. Common OO Applications • Computer-aided design (CAD) • Computer-aided manufacturing (CAM) • Geographic information systems (GIS) • Office Automation • Computer-aided publishing • Multimedia databases

  7. Non Conventional DBMS • Object Relational (Extend the Relational Model) • Construct an OODBMS from scratch • Knowledge Base Management Systems (OODBMS).

  8. Object Relational • Examples: Informix Universal Server (many OO features) Oracle (limited) MS-Access (very limited, picture field)

  9. 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).

  10. 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

  11. Oracle • Multivalued attributes using VARRAY • Object type • BLOB (Binary large object), CLOB (Characters), BFILE (Binary File), NCLOG (Intern. Characters) • 9i: Inheritance

  12. OODBMS references (products) • O2 http://o2tech.com • Gemstone http://www.gemstone.com • Objectstore http://www.odi.com • ITASCA http://www.iprolink.ch/ibex.com

  13. ORDBMS examples • Points, Lines and Circles • ASU: University DB Example

  14. Knowledge Base/Deductive DB • Expert System + Database Technology • Stores rules instead of data • Basically Prototypes available at Universities and Research Institutions

  15. Examples of Knowledge BaseDBMS Datalog (combines PROLOG + Database technology). http://goanna.cs.rmit.edu.au/~zahirt/Teaching/subj-datalog.html XSB http://www.cs.sunysb.edu/~kostis/Papers/xsb_ddb.html

  16. GIS Life Expectancy

  17. GIS Population

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