Architectural patterns are reusable solutions to common problems encountered in software architecture and design. These patterns provide a structured way to design and organize the components of a software system to achieve specific goals such as scalability, maintainability, and flexibility.
| Aspect | Design Patterns | Architectural Patterns |
|---|---|---|
| Scope | Class-level solutions | Overall structure of systems |
| Purpose | Address specific design issues | Organize entire systems |
| Granularity | Deal with classes or objects | Modules, components, relationships |
| Level of Abstraction | Low-level implementation | High-level system structure |
| Examples | Singleton, Factory Method, etc. | MVC, Microservices, etc. |
| Usage | Within a single application | For entire systems |
| Common Goals | Reusability, maintainability | Scalability, flexibility |
Description
Segregates the system into two applications, where the client makes requests to the server which then processes and returns the data.
Use Case
Web applications where the browser acts as the client and an application on a server handles the backend.
Description
Each node in the network acts as both a server and a client, eliminating the need for a centralized server.
Use Case
File-sharing systems like BitTorrent, blockchain applications.
vs. Client-Server
| Feature | Client-Server Architecture | Peer-to-Peer (P2P) Architecture |
|---|---|---|
| Basic Concept | Centralized server provides resources or services; clients consume these services. | Decentralized network where each peer acts as both client and server. |
| Network Structure | Centralized with one or more servers at the core. | Decentralized with no central server; all nodes are equal. |
| Scalability | Can be limited by the capacity of the server(s); requires scaling the server resources as demand increases. | Naturally scalable as each new peer adds to the network's capacity. |
| Resource Distribution | Server holds the resources, and clients request them. | Resources are distributed among peers; each peer can provide and consume resources. |
| Fault Tolerance | Single point of failure at the server; if the server goes down, the service is interrupted. | Highly resilient; if one peer fails, others can still operate and communicate. |
| Control and Management | Centrally managed by server administrators. | Lacks central management, which can lead to challenges in control and regulation. |
| Use Cases | Web servers, database servers, email servers, etc. | File sharing networks, blockchain and cryptocurrencies, certain streaming services. |
| Security | Security can be more straightforward to implement and manage due to centralized control. | Potentially more vulnerable to security risks due to its open and decentralized nature. |
Description
Separates system functionality into distinct layers that are stacked vertically on top of each other. Common layers include presentation, business logic, data access, and data storage.
Use Case
How a web application is internally structured on the server side. The application is divided into layers such as a front-end (for user interface), a business logic layer (where the main functionality of the application resides), and a data layer (for database interactions). Each layer has a specific responsibility and they communicate with each other in a defined order.
Description
Model: Manages data and business logic.
View: Handles the display and presentation of data.
Controller: Connects the Model and View, processing user input and responding to user actions.
Use Case
Web frameworks like Django and Ruby on Rails, desktop applications.
vs. Layered
| Aspect | MVC | Layered |
|---|---|---|
| Focus | User interface interactions | Organizational code structure |
| Components | Model, View, Controller | Presentation, Business Logic, Data Access Layers |
| Data Flow | Cyclical (View <-> Controller <-> Model) | Linear (Top to Bottom) |
| Use Cases | Web and GUI applications | Web, Desktop, Enterprise applications |
Description
Structures an application as a collection of loosely coupled services, which implement business capabilities.
Use Case
Large-scale enterprise applications that require high scalability and flexibility.
Description
Consists of services that communicate with each other. The communication can involve either simple data passing or it could involve two or more services coordinating some activity.
Use Case
Enterprise applications requiring integration of multiple disparate systems.
vs. Microservices
| Feature | Service-Oriented | Microservices |
|---|---|---|
| Scope | Enterprise-wide services, often larger and more generalized. | Smaller, lightweight services focused on specific business capabilities. |
| Communication | Often uses Enterprise Service Bus (ESB) for communication, which can become complex. | Uses simpler, decentralized communication mechanisms like RESTful APIs. |
| Service Size | Services are generally larger and can encompass broad business functionalities. | Services are smaller, highly specialized based on single business capability. |
| Technology Stack | Typically follows a standardized, often homogeneous technology stack. | Encourages the use of different technology stacks suitable for each service. |
| Integration and Coupling | Services are more tightly coupled and can share data storage. | Services are loosely coupled, each with its own data storage, ensuring high autonomy. |
| Development and Deployment | Development and deployment can be slower due to larger service size and shared dependencies. | Enables rapid, independent development and deployment of individual services. |
| Management and Scalability | Centralized management, which can be complex in large enterprises. | Easier to scale and manage due to smaller, independent services. |
| Use Cases | Suitable for large-scale enterprise applications requiring integration of various applications and systems. | Ideal for complex applications with requirements for rapid development, scalability, and resilience. |
Description
Builds the entire application as a single, indivisible unit.
Use Case
Simple applications with limited scalability and flexibility requirements.
Description
Centers around the production, detection, consumption of, and reaction to events.
Use Case
Real-time data processing applications, applications with asynchronous data flow.
Combining architectural patterns is a common practice in software design, allowing architects to leverage the strengths of multiple patterns to address complex requirements. Here are a few examples of how different architectural patterns can be combined.
In a microservices architecture, services can communicate with each other using events rather than direct calls. This decouples the services and reducing dependencies.
Event-driven architecture also enables microservices to react to changes in real-time. When an event occurs (like a data update), relevant microservices can immediately respond, making the system more dynamic and responsive.
By using events, microservices can handle requests asynchronously, improving system performance and scalability.
Layered Architecture can organize the internal structure of each SOA service, making it easier to manage and maintain.
Client-Server Architecture acts as the fundamental structure for network communication, where the client could be a web browser or mobile app, and the server is the application server hosting the business logic and data access layers.
Model-View-Controller Architecture organizes the server-side application structure. The server, in this combined architecture, likely implements the MVC pattern to manage data (Model), handle business logic (Controller), and serve the user interface (View).
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