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.