Software architecture: which one to use?

Software architectures are fundamental for building robust, scalable, and maintainable applications. Each architectural model offers specific advantages and disadvantages, and is designed to meet particular needs. The right choice depends on a range of factors, including project size, required scalability, and domain complexity. Below, we analyze five of the most widespread architectures and the contexts where each one fits best.

1. Client-Server architecture

The client-server model is one of the most traditional and widespread in modern computing. In this architecture, clients such as browsers, mobile apps, or desktop applications send requests to a central server that processes them and responds. The server is responsible for data management and business logic, while clients handle the user interface.

The centralization of resources is the main strength: the server becomes the focal point for access control and data management, simplifying maintenance and updates. The downside is dependence on a single node: if the server stops working, the entire system becomes unusable. This architecture adapts well to web platforms like online stores or internal corporate systems, where centralized management is a requirement rather than a compromise.

2. Layered architecture

Layered architecture divides the application into distinct layers, each with specific responsibilities. One layer handles the user interface, another the business logic, and another data access. This approach promotes separation of concerns, making the system more organized and facilitating testing and reusability of individual components.

Modularity has a cost, however: passing data through all the layers introduces computational overhead that can reduce performance in more complex applications. The rigid structure, with data required to traverse the entire hierarchy, can become a bottleneck in highly scalable systems. The layered model remains the natural choice for management applications, e-learning platforms, and multi-user software, where structural clarity matters more than raw speed.

3. Pipes and filters

The pipes and filters architecture is inspired by industrial processes: data passes through a sequence of transformations called filters, connected by pipelines. Each filter performs a specific function, such as raw data processing, normalization, or conversion, and can be replaced or reused independently of the others.

The great modularity of this model makes it easy to extend: adding a new filter to the pipeline does not require touching the rest of the system. However, the overhead involved in managing pipelines and the fragmentation of processes can reduce performance and complicate debugging, especially with large data volumes. This model is particularly suited to multimedia processing systems, ETL pipelines for business data, and complex transformations in scientific or financial contexts.

4. Domain-Driven Design (DDD)

Domain-Driven Design is a paradigm that places the business domain at the center, meaning the specific rules and processes of the organization. The application is divided into bounded contexts, each representing a well-defined functional area such as order management or the product catalog. This approach fosters a common language between developers and stakeholders, improving communication and reducing misinterpretation.

DDD requires careful initial planning and a team with solid knowledge of the application domain. The entry cost is high, and implementing it without the right experience can introduce unnecessary complexity. The contexts where it excels are ERP systems, e-commerce platforms with multiple domains such as catalog, orders, and payments, and financial applications with intricate business rules.

5. Monolithic architecture

Monolithic architecture is the simplest to picture: all the application’s code is contained in a single block, deployed in a single operation. This approach reduces infrastructural complexity and eases integration between components, making it ideal in the early stages of a project.

As the application grows, however, this simplicity becomes a constraint. Making changes or scaling a single part requires touching the entire system, with increasing risk of regressions. Even so, the monolithic model remains the most sensible choice for prototypes and MVPs, small-scale applications, and small teams, where development speed and operational simplicity matter more than long-term flexibility.

Choosing the right architecture requires careful analysis of a project’s priorities. Models like client-server and layered offer simplicity and modularity, DDD brings clarity to complex systems, while pipes and filters excels in data transformation pipelines. The monolith remains a solid starting point when speed is everything. The important thing is to balance functional needs, technical implications, and team capabilities, choosing the architecture that best supports the maintenance and evolution of the system over time.