History of Database Systems

Data are raw facts that constitute building blocks of information.  Database is a collection of information and a means to manipulate data in a useful way, which must provide proper storage for large amounts of data, easy and fast access and facilitate the processing of data.  Database Management System (DBMS) is a set of software that is used to define, store, manipulate and control the data in a database. From pre-stage flat-file system, to relational and object-relational systems, database technology has gone through several generations and its 40 years history.

 The Evolution of the Database

 Ancient History: Data are not stored on disk; programmer defines both logical data structure and physical structure, such as storage structure, access methods, I/O modes etc. One data set per program: high data redundancy.  There is no persistence; Random access memory (RAM) is expensive and limited, programmer productivity low. 

1968 File-Based: predecessor of database, Data maintained in a flat file.  Processing characteristics determined by common use of magnetic tape medium.

• Data are stored in files with interface between programs and files. Mapping happens between logical files and physical file, one file corresponds to one or several programs
• Various access methods exits, e.g., sequential, indexed, random
• Requires extensive programming in third-generation language such as COBOL, BASIC.
• Limitations:
  • Separation and isolation: Each program maintains its own set of data, users of one program may not aware of holding or blocking by other programs.
  • Duplication: Same data is held by different programs, thus, wastes space and resources.
  • High maintenance costs such as ensuing data consistency and controlling access
  • Sharing granularity is very coarse
  • Weak security

1968-1980 Era of non-relational database: A database provides integrated and structured collection of stored operational data which can be used or shared by application systems.  Prominent hierarchical database model was IBM�s first DBMS called IMS. Prominent network database model was CODASYL DBTG model; IDMS was the most popular network DBMS.

 Hierarchical data model

• Mid 1960s Rockwell partner with IBM to create information Management System (IMS), IMS DB/DC lead the mainframe database market in 70�s and early 80�s.
• Based on binary trees. Logically represented by an upside down tree, one-to many relationship between parent and child records.
• Efficient searching; Less redundant data; Data independence; Database security and integrity
• Disadvantages:
  • Complex implementation
  • Difficult to manage and lack of standards, such as problem to add empty nodes and can�t easily handle many-many relationships.
  • Lacks structural independence, such add up application programming and use complexity.

 Network data model

• Early 1960s, Charles Bachmann developed first DBMS at Honeywell, Integrated Data Store ( IDS)
• It standardized in 1971 by the CODASYL group (Conference on Data Systems Languages)
• Directed acyclic graph with nodes and edges
• Identified 3 database component: Network schema�database organization; Subschema�view s of database per user; Data management language -- at low level and procedural
• Each record can have multiple parents:
  • Composed of sets relationships, a set represents a one--many relationship between the owner and the member
  • Each set has owner record and member record
  • Member may have several owners
• Main problem: System complexity and difficult to design and maintain; Lack of structural independence

The distinction of storing data in files and databases is that databases are intended to be used by multiple programs and types of users.

1970-present Era of relational database and Database Management System (DBMS): Based on relational calculus, shared collection of logically related data and a description of this data, designed to meet the information needs of an organization; System catalog/metadata provides description of data to enable program-data independence; logically related data comprises entities, attributes, and relationships of an organization�s information. Data abstraction allows view level, a way of presenting data to a group of users and logical level, how data is understood to be when writing queries.

• 1970: Ted Codd at IBM�s San Jose Lab proposed relational models.
• Two major projects start and both were operational in late 1970s
  • INGRES at University of California, Berkeley became commercial and followed up POSTGRES which was incorporated into Informix.
  • System R at IBM san Jose Lab, later evolved into DB2, which became one of the first DBMS product based on the relational model. (Oracle produced a similar product just prior to DB2.)
• 1976: Peter Chen defined the Entity-relationship(ER) model
• 1980s: Maturation of the relational database technology, more relational based DBMS were developed and SQL standard adopted by ISO and ANSI.
• 1985: Object-oriented DBMS (OODBMS) develops.  Little success commercially because advantages did not justify the cost of converting billions of bytes of data to new format.
• 1990s: incorporation of object-orientation in relational DBMSs, new application areas, such as data warehousing and OLAP, web and Internet, Interest in text and multimedia, enterprise resource planning (ERP) and management resource planning (MRP)
  • 1991: Microsoft ships access, a personal DBMS created as element of Windows gradually supplanted all other personal DBMS products.
  • 1995: First Internet database applications
  • 1997: XML applied to database processing, which solves long-standing database problems.  Major vendors begin to integrate XML into DBMS products.

  

Relational DBMS at glance:

Fundamental  Relational Database Characteristics	Database Schema(The description of the user data in the database)	DBMS Functions	Database Approach	Advantages and disadvantages of DBMSs
�          The internal structure of an operating database is basically fixed in the �row� direction �          The user will interact with a logical view of the data, and need not know anything about the actual internal structure.	�          Conceptual schema: logically describes all data in the database �          Internal schema (Physical schema): describes how data are actually stored. �          External schema (User view): describes the data which are interested by user.	�          Data dictionary management �          Data storage management �          Data transformation and presentation �          Security management �          Multi-user access control �          Backup and recovery management �          Data integrity management �          Database language and application programming interfaces �          Database communication interfaces	�          Data definition language (DDL): define database schemas �          Data manipulation language (DML): to retrieve, insert, delete and update data in the database. Query language are part of DML �          Data control language (DCL): control the access of data.	Advantages: �          Control of data redundancy, consistency, abstraction, sharing �          Improved data integrity, security, enforcement of standards and economy of scale. �          Balanced conflicting requirements �          Improved data accessibility, responsiveness, maintenance �          Increase productivity, concurrency, backup and recovery services. Disadvantages:  �          Complexity, size, cost of DBMSs �          Higher impact of a failure

• The main players:
  • Microsoft Corp- SQL Server
  • Oracle- Oracle 9i
  • IBM � IMS/DB, DB2

Relational companies challenged by �object-oriented DB� companies, and countered with �object-relational� systems, which retain the relational core while allowing type extension as in OO systems.

 The advanced database technology, along with Internet has proved faster communication and world-wide connectivity, ubiquitous publishing seems led information overload, and still, I can�t find a thing!