Classification of Database Management Systems

Classification of Database Management Systems (DBMS)

• Introduction to DBMS:

  • DBMS facilitates front-end communication with multiple back-end databases.
  • Encryption technology enhances the security of sensitive data transfer between clients and servers.

• Data Models:

  • Relational Model:
  • Most prevalent model in commercial DBMSs, based on tables.
  • SQL systems utilize this model for data management.
  • Object Data Model:
  • Less common in commercial use, defines data in terms of objects and their operations.
  • Big Data Systems:
  • Includes NOSQL and key-value systems using various models:
    • Document-based
    • Graph-based
    • Column-based
    • Key-value
  • Legacy Models:
  • Hierarchical and network models still in use for legacy applications.
  • Object-Relational DBMSs:
  • Evolution from relational to incorporate object-oriented concepts.
  • Native XML DBMS:
  • Implements XML as a tree-structured model, allowing for advanced storage options.

• User Support:

  • Single-User Systems:
  • Designed for one user, typically on PCs.
  • Multiuser Systems:
  • Support concurrent access by multiple users, widely used in DBMSs.

• Distribution:

  • Centralized DBMS:
  • All data stored at one site.
  • Distributed DBMS (DDBMS):
  • Data distributed across sites.
  • Can be Homogeneous (same software across sites) or Heterogeneous (different software).
  • Middleware can manage access to autonomous databases in heterogeneous systems.

• Cost Considerations:

  • Open Source Options:
  • MySQL and PostgreSQL are free, supported by third-party vendors.
  • Commercial DBMSs:
  • Price varies from free trial versions to expensive complex systems costing millions annually.
  • Licenses can limit concurrent users or provide site-wide access.

• Access paths:

  • Inverted File Structures:
  • Commonly used structure for DBMSs to enable efficient file storage.

• General vs. Special-Purpose DBMS:

  • General-Purpose:
  • Versatile, used in various applications.
  • Special-Purpose:
  • Designed for specific tasks, e.g., airline reservations; falls under Online Transaction Processing (OLTP).

• Relational Data Model Details:

  • Represents data in tables, allows relationships using foreign keys.
  • Uses structured queries via SQL; chapters 5–8 cover relational operations.

• Object Data Model:

  • Defines data as objects within classes, which support methods and properties.
  • Hierarchies determine class relationships; discussed further in Chapter 12.

• Big Data Models:

  • Key-Value Model:
  • Associative structure for rapid data retrieval.
  • Document Model:
  • JSON storage format for flexible data representation.
  • Graph Model:
  • Represents data as nodes/edges to depict relationships.
  • Column-Based Models:
  • Organizes data in columns for efficient access.

• XML Model:

  • Key in data exchange over the internet, using a hierarchical tree structure.
  • Integrates database and document representation concepts.

• Legacy Data Models:

  • Network Model:
  • Uses pointers for record relationships; highlighted by the CODASYL DBTG model.
  • Hierarchical Model:
  • Data structured in trees; dominated DBMS from 1965 to 1985.

• This classification provides a comprehensive overview of how DBMSs are structured and categorized, important for database technology understanding and implementation.