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Different Types of Common System Architecture

System architecture refers to the structure and design of a system, defining how its components interact to deliver functionality. There are several common types of system architectures, each suited to specific use cases, complexities, and business requirements.

 

1. Monolithic Architecture

  • Definition: The entire system is built as a single, unified unit where all components (UI, business logic, data access) are tightly integrated.
  • Characteristics:
    • One large codebase.
    • Simple to develop initially but harder to scale and maintain.
  • Use Cases:
    • Small-scale applications.
    • Systems with low complexity and infrequent updates.
  • Examples: Traditional web applications built on early frameworks like ASP.NET or Ruby on Rails.

2. Layered (Tiered) Architecture

  • Definition: Divides the system into layers (tiers), each with a specific role, such as presentation, business logic, and data access.
  • Characteristics:
    • Commonly follows the 3-tier model: Presentation, Business Logic, Data.
    • Layers are loosely coupled.
  • Use Cases:
    • Enterprise applications with structured workflows.
    • Scalable web apps requiring clear separation of concerns.
  • Examples: E-commerce websites, ERP systems.

3. Client-Server Architecture

  • Definition: A system where clients (front-end devices) request services or data from a server (back-end system).
  • Characteristics:
    • Centralized control (server) with multiple clients.
    • Suitable for distributed environments.
  • Use Cases:
    • File-sharing systems, email systems, or database-driven apps.
  • Examples: Web browsers communicating with web servers.

4. Microservices Architecture

  • Definition: A system design where functionalities are broken into small, independent services that communicate over APIs.
  • Characteristics:
    • Highly modular and scalable.
    • Each service can use different technologies and be deployed independently.
  • Use Cases:
    • Large-scale, complex applications requiring agility.
    • Applications with frequent updates and diverse functionalities.
  • Examples: Netflix, Amazon, Uber.

5. Event-Driven Architecture

  • Definition: A system design where components communicate by producing and consuming events, often using an event broker or bus.
  • Characteristics:
    • Reactive and real-time communication.
    • Decouples event producers from consumers.
  • Use Cases:
    • Systems requiring high responsiveness, like IoT applications.
    • Streaming platforms and financial transaction systems.
  • Examples: Stock trading platforms, Kafka-based systems.

6. Service-Oriented Architecture (SOA)

  • Definition: An architecture style where system components are delivered as reusable services, often exposed through a service bus.
  • Characteristics:
    • Services are loosely coupled.
    • Focuses on reusability and interoperability.
  • Use Cases:
    • Enterprise-level integration of legacy systems.
    • Scenarios requiring a focus on reusing business logic.
  • Examples: Banking systems, healthcare systems with HL7.

7. Serverless Architecture

  • Definition: A cloud-native architecture where the application is built on functions executed on demand, with no need for server management.
  • Characteristics:
    • Pay-as-you-go model for execution.
    • Scales automatically based on demand.
  • Use Cases:
    • Lightweight, event-driven applications.
    • Systems with sporadic workloads.
  • Examples: AWS Lambda, Azure Functions.

8. Peer-to-Peer (P2P) Architecture

  • Definition: A decentralized system where nodes (peers) interact directly with one another without a central server.
  • Characteristics:
    • Resilient and fault-tolerant.
    • No single point of failure.
  • Use Cases:
    • File-sharing systems, blockchain applications.
  • Examples: BitTorrent, Bitcoin.

9. Distributed Architecture

  • Definition: A system where components are distributed across multiple locations and communicate over a network.
  • Characteristics:
    • High availability and fault tolerance.
    • Complex to manage and debug.
  • Use Cases:
    • Systems requiring scalability and high reliability.
    • Real-time data processing systems.
  • Examples: Hadoop, distributed databases like Cassandra.

10. Modular / Domain Architecture

  • Definition: A system composed of interchangeable, self-contained modules that work together.
  • Characteristics:
    • Highly maintainable and adaptable.
    • Supports plug-and-play functionality.
  • Use Cases:
    • Systems requiring flexibility and adaptability.
    • Systems with evolving requirements.
  • Examples: IoT systems with modular sensors.

11. Component-Based Architecture

  • Definition: A design that organizes the system into reusable components that encapsulate functionality and interact through interfaces.
  • Characteristics:
    • Encourages reusability and separation of concerns.
    • Components can be developed and tested independently.
  • Use Cases:
    • Software with reusable parts, such as UI libraries.
  • Examples: React.js, Angular.

12. Hybrid Architecture

  • Definition: A combination of multiple architectural styles to meet specific requirements.
  • Characteristics:
    • Tailored to the application's needs.
    • Can be complex to design and maintain.
  • Use Cases:
    • Complex applications requiring diverse functionality.
    • Systems with varying workloads.
  • Examples: A system using microservices for core functions and serverless for auxiliary tasks.

Choosing the Right Architecture

The selection depends on:

  1. Scale of the Application: Small, medium, or large-scale.
  2. Complexity: Single-functionality vs. multi-functional systems.
  3. Performance Needs: Real-time processing vs. batch processing.
  4. Future Growth: Scalability and modularity requirements.
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