Legacy DB Systems
- File Processing Systems
- Hierarchical Model
- Network Model
Legacy Database Systems
Legacy database systems played a crucial role in the evolution of data management, paving the way for more advanced relational database systems.
Legacy Database Systems, including
- File Processing Systems
- Hierarchical Model
- Network Model,.
1. File Processing Systems
Definition:
File Processing Systems are traditional data management systems that use flat files to store and manage data. In this approach, each department or user group maintains its own set of files, leading to data redundancy.
Characteristics:
Data stored in flat files.
No centralized control or structure.
Limited data sharing and integration.
Advantages:
Simplicity: Easy to implement and understand.
Independence: Each department has control over its data.
Cost: Relatively low implementation and maintenance costs.
Performance: Can be efficient for specific tasks.
Flexibility: Each department can choose its file organization.
Disadvantages:
Data Redundancy: Multiple copies of the same data in different files.
Inconsistency: Difficulty in maintaining data consistency.
Data Isolation: Limited data sharing between departments.
Security: Limited access controls.
Lack of Standards: No standardized data formats.
Examples:
Filing cabinets with paper records.
Spreadsheet files stored on individual computers.
Text files storing data for different applications.
2. Hierarchical Model:
The Hierarchical Model organizes data in a tree-like structure, with a single root representing the entire database and branches representing different entities and their relationships. It was widely used in early database management systems.
Characteristics:
Organized in a tree structure.
Parent-child relationships between records.
Navigational access through tree traversal.
Advantages:
Data Integrity: Ensures data relationships.
Efficiency: Can be efficient for certain types of queries.
Simplicity: Simple and intuitive structure.
Security: Access control through parent-child relationships.
Integrity Constraints: Enforces relationships.
Disadvantages:
Lack of Flexibility: Not suitable for all types of relationships.
Complexity in Querying: Complex queries require navigating the hierarchy.
Maintenance Overhead: Changes to the structure can be cumbersome.
Limited Scalability: Difficult to scale for larger datasets.
Data Redundancy: Redundant data due to hierarchical structure.
Examples:
IMS (Information Management System).
Windows Registry (in a hierarchical structure).
3. Network Model
The Network Model represents data as records connected through links or pointers, allowing for more complex relationships than the hierarchical model. It supports many-to-many relationships.
Characteristics:
Records are connected through links.
Supports many-to-many relationships.
Complex navigational structures.
Advantages:
Data Integrity: Maintains data relationships.
Flexibility: Supports complex relationships.
Efficiency: Can be efficient for certain types of queries.
Data Independence: Changes in the database structure do not affect applications.
Security: Access control through record-level permissions.
Disadvantages:
Complexity: Complex structure and navigational paths.
Query Complexity: Writing queries can be intricate.
Maintenance Overhead: Changes to the structure can be challenging.
Lack of Standards: Not widely standardized.
Limited Adoption: Superseded by relational databases.
Examples:
CODASYL (Conference on Data Systems Languages).
IDMS (Integrated Database Management System).
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