DBMS architecture, data Models and database approach

Characteristics of Database Approach

Data Independence

• DBMS allows separation between the physical storage of data and the way users perceive it.
• Example: If the structure of a table changes, applications relying on it won't be affected.
• Data independence enhances system flexibility, making it easier to adapt to evolving business needs.

Data Integrity

• Data integrity Ensures accuracy and consistency of data by enforcing constraints and rules.
• Example: A database might enforce a unique constraint on an employee ID to prevent duplicates.
• Referential integrity ensures relationships between tables are maintained, preventing orphaned records.

Data Security

• DBMS provides mechanisms to control access to data, ensuring only authorized users can manipulate it.
• Example: Role-based access control restricting certain users from modifying sensitive information.
• Auditing features track user activities, aiding in identifying and addressing security breaches.

Concurrency Control

• Manages simultaneous access to data to prevent conflict and ensure consistency
• Example: Two users attempting to modify the same record simultaneously - DBMS ensures one operation is completed before the other.
• Techniques like locking and timestamp-based methods help maintain data consistency in multi-user environments.

Data Redundancy Reduction

•  Minimizes data duplication, saving storage space and reducing the risk of inconsistencies.
• Example: Storing customer information in a separate table linked by a unique identifier instead of duplicating it in every order entry.
•  Normalization is a technique used to eliminate redundancy by organizing data in a structured manner.

Query Language

•  DBMS offers a query language (e.g., SQL) for users to interact with the database.
• Example: Using SQL SELECT statements to retrieve specific data from a table.
•  Advanced query optimization techniques enhance the efficiency of data retrieval operations.

DBMS Architecture

• Three-Tier Architecture (Client/Server Model)
• Centralized Architecture
• Distributed Architecture
• Peer to Peer Architecture

Three-Tier Architecture (Client/Server Model)

• Divides the DBMS into three components - client, application server, and database server.
• Example: An application (client) communicates with the server, which manages interactions with the database server.

Presentation Layer

• The first tier that interacts with users and displays information through a user interface.
• Example: Web browsers or applications used by users to access and view data.

Logic/Processing Layer

• The second tier that handles data processing, business logic, and application functionalities.
• Example: Application servers or middleware that execute operations based on user requests.

Data Layer

• The third tier where data storage and management occur, often using database servers.
• Example: Database management systems (DBMS) like MySQL, PostgreSQL, or Oracle used to store and retrieve data.
•  This architecture facilitates scalability, allowing the system to handle a growing number of users and data.

Centralized Architecture

•  All components, including the database, are on a single machine.
• Example: Small-scale systems where a single server handles both application processing and database management.
• All data management tasks, including updates and backup , are centralized in one location.
•  Centralized architectures are easier to manage but may face limitations in terms of scalability and fault tolerance.

Distributed Architecture

• Components are distributed across multiple machines, providing scalability and fault tolerance.
• Example: Large-scale systems where different servers handle specific tasks, enhancing performance and reliability.
•  Load balancing techniques ensure even distribution of workload among the distributed servers.
• Distributed architecture allows for data replication and synchronization among nodes to maintain data consistency.
• Example: Replicating customer data across multiple servers to ensure availability and reliability.

Peer to Peer Architecture

• In a peer-to-peer architecture, all network nodes have equal status and can function as both clients and servers.
• Example: File-sharing networks like BitTorrent, where users can upload and download files directly from other users' devices.
• Data management tasks are decentralized, with each node responsible for storing and sharing a portion of the data.
• Example: Blockchain networks like Ethereum or Bitcoin, where nodes collectively maintain a distributed ledger of transactions.
•  Peer-to-peer architectures often lead to better fault tolerance as there is no single point of failure.

Data Models

• Relational Data Model
• Hierarchical Data Model
• Network Data Model
• Object Oriented Data Model
• Document Data Model

Relational Data Model

•  Represents data as tables with rows and columns, establishing relationships between them.
• Example: A database containing tables for employees, departments, and projects linked by common keys.
• Normalization techniques help maintain data integrity by eliminating data anomalies.

Hierarchical Data Model

•  Represents data in a tree-like structure with parent-child relationships.
• Example: Organizing organizational data with a CEO at the top, followed by departments, teams, and employees.
• Hierarchical models are suitable for representing certain real-world hierarchical relationships, but they may lack flexibility because.
• Example: Adding a new department or rearranging the hierarchy may involve significant modifications to the existing model.

Network Data Model

•  Similar to the hierarchical model but allows multiple parent-child relationships.
• Example: A university database with students linked to multiple courses and instructors.
•  This model supports more complex relationships, but it can be challenging to design and maintain.

Object Oriented Data Model

• In  Represents data as objects, combining data and methods.
• Example: A multimedia database storing images, videos, and audio as objects with associated methods.
• Object-oriented models are well-suited for systems where real-world entities can be represented as objects.

Document Data Model

•  Stores data in flexible, JSON-like documents, suitable for semi-structured data.
• Example: A content management system storing articles as documents with varying fields.
• Document-oriented databases excel in handling unstructured or semi-structured data, providing flexibility in schema design.

Conclusion