DBMS ARCHITECTURE
the architecture of a typical Database Management System (DBMS):
1. Three-Tier Architecture:
- Presentation Tier (Client Tier): This tier interacts directly with the users and provides them with the interface to interact with the DBMS.
- Application Tier (Middle Tier): This tier contains the application logic that processes user requests, performs validations, and communicates with the database.
- Data Tier (Database Tier): This tier consists of the actual database where data is stored, managed, and retrieved. It includes the database server and related software.
2. Components of Data Tier:
- Database Server: This is the core component that manages the storage, retrieval, and manipulation of data. It includes the Database Management System software.
- Storage Engine: Responsible for managing how data is stored on disk and retrieved into memory.
- Query Processor: Handles user queries, translates them into low-level instructions, and optimizes query execution for efficient data retrieval.
- Transaction Manager: Ensures the ACID properties (Atomicity, Consistency, Isolation, Durability) of database transactions.
- Concurrency Control: Manages simultaneous access to the database by multiple users to ensure data consistency and integrity.
3. Key Functionalities:
- Data Definition: Allows defining the structure of the database, including tables, relationships, constraints, etc.
- Data Manipulation: Provides mechanisms to insert, update, delete, and retrieve data from the database.
- Data Control: Enforces security measures such as authentication, authorization, and access control.
- Data Integrity: Maintains data consistency and validity through constraints, triggers, and validation rules.
Recommended by LinkedIn
- Concurrency Control: Handles simultaneous access to the database to prevent conflicts and ensure data consistency.
4. Deployment Options:
- On-Premises: The DBMS is installed and managed on the organization's own infrastructure.
- Cloud-Based: The DBMS is hosted and managed by a third-party cloud service provider, offering scalability and flexibility.
- Hybrid: Combination of on-premises and cloud-based deployment to leverage the benefits of both approaches.
### 5. Scalability and Performance:
- Vertical Scaling: Adding more resources (CPU, memory) to the existing server to handle increased workload.
- Horizontal Scaling: Distributing the workload across multiple servers to handle increased traffic and data volume.
- Indexing and Query Optimization: Techniques to optimize query execution for improved performance.
- Caching: Storing frequently accessed data in memory for faster retrieval.
- Partitioning: Dividing the database into smaller partitions to distribute data and workload efficiently.
#snsinstitutions
#snsdesignthinker
#designthinking