History of Database Systems

1
History of Database Systems

• File systems (before mid 1960s)
• Problems Data redundancy
• update anomalies
• no abstract data model
• requires knowledge of
  storage details
• no standard query language

2
Hierarchical Databases (mid 1960s)

• Developed by North American Rockwell and IBM
• as the IMS (Information Management System)
• Based on a tree structure
• Example A Product assembled from components,
  which are assembled from subcomponents
• Problems Changes in data structure require
  changes
• in application programs that access that
  structure
• No Many-to-Many relationships
• Programmers must be thoroughly familiar with
  the
• database structure.

3
Network Databases

• Extension of the hierarchical data model
• Standardized (1971) by the CODASYL group
  (Conference on Data Systems Languages)
• Advantage Many-to-Many relationships are
  implemented
• Problems Navigation is even harder

4
Relational Databases

• Proposed in 1970 by E.F. Codd while working at
  IBM.
• IBM largely ignored his work, as the company was
  investing heavily at the time in commercializing
  IMS databases.
• It was not until 1978 that Frank T. Cary, then
  chairman and CEO of IBM ordered the company to
  build a product based on Dr. Codds ideas.

5

• But IBM was beaten to the market by Lawrence J.
  Ellison, a Silicon Valley entrepreneur, who used
  Dr. Codds papers as the basis of a product
  around which he built a start-up company that has
  since become the Oracle Corporation.
• New York Times April 23, 2003
• Obituary of E. F. Codd
  (1923-2003)

6
1. Relational Databases

• Data Abstraction- allows people to forget
• unimportant details
• View Level a way of presenting data to a
• group of users
• Logical Level how data is understood to be
• when writing queries

7

• 1.1 The View Level
• Examples
• Charts
• Graphs
• Drawings
• Maps

8

• 1.2 The Logical Level
• Example
• Infinite relational data model
• Relation table
• Relational schema top row / list of attributes
• Arity number of attributes
• Database schema set of relation names and
  schemes
• Tuple / Point each row below the scheme
• Instance the set of tuples in a table

9

• Relation schemes are usually fixed
• Relation instances change with updates
• Example Scheme
• Taxrecord(SSN,Wages,Interest,Capital_gain)
• Taxtable(Income,Tax)

10

• Example
• Streets(Name, X, Y )
• Streets contains pairs of street names and (x,y)
  points such that the point belongs to the street.
  There are an infinite number of (x, y) locations
  associated with each street.
• Example
• Crops(Corn,Rye,Sunflower, Wheat)
• Crops contains all possible combinations of
  four crops that a farmer could plant. There are
  an infinite number of tuples in any instance of
  this relation.

11

• 1.3 Abstract Data Types
• Domain range of values for an attribute.
• string, integers or real numbers
• Scalar Domain always a single value
• (ex string, integer
  or real number)
• Abstract data type domains composed of scalar
• 
  domains.

12

• Example
• Vertices(Cities)
• The domain of Cities is a set of
  strings.
• Example
• Streets(Name, Extent)
• The domain of Extent is a set of (x,y)
  points.