Software Architecture Styles Summary

Layered Architecture

Concept

Organizes software into distinct layers like presentation, business logic, and data access. Each layer is responsible for a specific aspect and interacts only with its neighboring layers.

Pros

• Clear separation of concerns• Modularity and easier maintenance• Supports team parallelism

Cons

• Tight coupling between layers• Difficult to scale specific components

Use Case

Enterprise applications, web and desktop software

Technology Stack

Java (Spring MVC), .NET, Angular + Express.js, MySQL/PostgreSQL

Component-Based Architecture

Concept

Constructs systems from interchangeable, reusable components with well-defined interfaces.

Pros

• High modularity• Supports independent deployment and updates• Encourages reuse

Cons

• Complex dependency and integration management

Use Case

Plugin-based systems, UI component libraries

Technology Stack

React, Vue.js, Angular (components), OSGi, Webpack

Service-Oriented Architecture (SOA)

Concept

Builds applications from services that interact over a network using standardized protocols like SOAP or REST.

Pros

• Interoperability• Reusability of services• Scalable architecture

Cons

• Performance overhead• Requires strong governance

Use Case

Enterprise integration, B2B systems

Technology Stack

Java EE (JAX-WS), .NET WCF, Apache CXF, MuleSoft, Oracle SOA Suite

Domain-Driven Design (DDD)

Concept

Focuses on creating software models that reflect complex business domains using entities, aggregates, and value objects.

Pros

• Aligns code closely with business needs• Supports modular scaling via bounded contexts

Cons

• High learning curve• Requires close domain expert collaboration

Use Case

Complex business applications like finance or healthcare

Technology Stack

Spring Boot, Axon Framework, .NET Core, EventStoreDB

Event-Driven Architecture

Concept

Allows components to communicate by sending and receiving events, enabling asynchronous and loosely coupled systems.

Pros

• Scalable and responsive• Decouples producers and consumers

Cons

• Harder to trace and debug• Eventual consistency challenges

Use Case

IoT platforms, real-time analytics, microservices

Technology Stack

Apache Kafka, RabbitMQ, NATS, AWS SNS/SQS, Spring Cloud Stream, Akka

Separation of Concerns (SoC)

Concept

Divides a program into sections with distinct responsibilities, improving structure and maintainability.

Pros

• Improved clarity and maintainability• Simplified testing and debugging

Cons

• Risk of over-engineering and unnecessary complexity

Use Case

MVC-based web apps, layered applications

Technology Stack

Django, ASP.NET MVC, Ruby on Rails, Laravel

Interpreter Architecture

Concept

Executes instructions from domain-specific languages (DSLs) or scripts at runtime using an interpreter.

Pros

• Supports dynamic behavior• Flexible and configurable

Cons

• Slower than compiled approaches• More complex to build and optimize

Use Case

Scripting engines, rule engines, configuration interpreters

Technology Stack

ANTLR, Python (eval), JavaScript (V8), Drools

Concurrency Architecture

Concept

Supports parallel execution using threads, processes, or actor models to improve responsiveness and throughput.

Pros

• Efficient hardware utilization• High performance and scalability

Cons

• Risks like deadlocks and race conditions• Difficult to debug and test

Use Case

Real-time processing, high-performance systems

Technology Stack

Akka, Java Concurrency API, .NET TPL, Node.js, Go routines

Data-Centric Architecture

Concept

Centers system design around data and its flow, ideal for data-heavy operations and analytics.

Pros

• Efficient data processing• Scalable and optimized for analytics

Cons

• Logic tightly coupled to data models• Less flexibility in business logic abstraction

Use Case

ETL systems, data lakes, BI platforms

Technology Stack

Apache Hadoop, Apache Spark, SQL Server, Talend, Snowflake