Pick the Most Suitable Software Architecture for Your Enterprise App: Complete Comparison

Are you thinking of starting a brand new software project? Or have you ever wondered how great business systems are designed? 

Before major software development begins, you must choose the right software architecture that will deliver the desired functionality and quality attributes.

If you are choosing the latest or most popular technology on the market, it will not always mean the best results. However, this also should not motivate you to opt for legacy technologies.

For instance, let us suppose there is a project that involves creating a regular data entry form (with less than 15 fields) for a particular survey. This data will be used only once by less than 100 users. Then using a highly complex architecture for this can result in total disaster.

Careful planning must be done when selecting an architecture pattern and the following characteristics should be considered:

• Budget
• Time to buy
• Number of users (current and future)
• Isolation level (i.e. integration with other platforms/systems)
• Tolerance time for system unavailability

In this article, I have summarized the five software architectures in a quick reference of strengths and weaknesses, as well as optimal use cases.

Point to be noted here is that you are free to use multiple patterns in one software to optimize each section of code with the best architecture. 

Although they call it computing, for me it is an art!

1. Layered Architecture

One of the most efficient and common models implemented by companies is Layered Architecture. The layers of this model are not interdependent, but are interconnected with each other. This is the general method of designing most software.

For example, if you want to change from an Oracle database to a SQL one. This change may cause it to stand out at the database layer, but it will not have a ripple effect on any other layer, thus avoiding failure.

What does it solve?

It allows you to segment your software in such a way that modules can evolve and develop separately with few dependencies between parts, allowing for reuse, modifiability, and portability. The layer pattern divides the software into units called layers. Each layer that you see is a grouping of modules. It is this module that provides us with a cohesive set of services.

Benefits:

• This architecture helps those companies that do not want to go overboard with experimentation and want to stick to conventional software architecture design patterns.
• Testing components becomes relatively easier since the interdependencies are negligible in this software development engineering format.

Warnings:

• Larger applications tend to be resource intensive if based on this format, therefore for such projects it is recommended to ignore the layered pattern.
• The full version of the software installs as a single unit independent of separate layers. Therefore, you will have to reinstall the entire device again, even if you update a single layer.

Better for:

• New applications that must be created quickly.
• General desktop applications.
• Teams with less experienced developers who do not yet understand other architectures.
• Applications that require strict standards for testability and maintenance.

2. Event-driven Architecture

Many software programs are not smart enough and spend the majority of their time waiting for something to happen. This is generally the case with the computers that work directly with humans, but it is also common in areas such as networks. Sometimes there is data that needs processing and sometimes not.

The event-driven architecture helps manage this by building a central unit that accepts all the data and then delegates it to separate modules that handle the particular type. This transfer is said to generate an "event" and is delegated to the code assigned to that type.

Programming a web page with JavaScript involves writing small modules that react to events such as mouse clicks or keystrokes. 

The browser itself organizes all input and makes sure that only the correct code sees the correct events. Many different types of events are common in the browser, but modules interact only with events that concern them. 

This is very different from the layered architecture where all the data will normally pass through all the layers. In general, event-driven architectures:

• They easily adapt to complex, often chaotic environments.
• Scale easily
• They are easily expandable when new types of events appear.

Warnings:

• Testing can be complex if modules can affect each other. While individual modules can be tested independently, interactions between them can only be tested on a fully functioning system.

• Error handling is quite complicated to structure. Thi happens especially when there are multiple modules that must handle the same line of events.

• When these modules fail to respond, the central unit or the brain must have a backup action plan.

• Messaging overhead can slow processing speed, especially when the central unit must store messages that arrive in bursts.

• Developing a data structure for system-wide events can be complex when events have very different needs.

• Maintaining a transaction-based consistency mechanism is complicated. The reason behind this is that the modules are highly decoupled and independent in nature.

Better for:

• Asynchronous systems with asynchronous data flow
• Applications where individual data blocks interact with only some of the many modules
• User interfaces

3. Microservices Architecture

Microservices are a self-regulating code base which is independent in nature and can be written by even a small team of developers. 

The microservices architecture consists of independent services, and each service is responsible for the implementation of its related business logic.

These independent services are separated from each other based on the nature of their domains and belong to a group of mini-microservices. 

When you hire mobile app programmers in India, you can take advantage of the capabilities of this architecture, especially for complex applications.

What does it solve?

Monolithic applications become too complex and large for efficient support and deployment for distributed resource utilization, such as in cloud environments.

Microservices help build applications as sets of services. Each service is scalable and deployable independently and has its API layer. 

Different teams can develop different services, manage your database, and write in different programming languages.

Benefits:

• This architecture design pattern makes the system highly fault tolerant as services are segmented into groups. In other words, all software will not fail even if some microservices stop working.
• It allows scaling applications. Independent services lead to individual scaling rather than burdening the entire system with the need to expand.
• The services can be combined in any application depending on the scope of work.

Warnings:

• More difficult to understand because of its complex logic. It requires a deep analysis in the decomposition of the service.

Better for:

• Websites with small components.
• Corporate data centers with well-defined boundaries.
• Rapidly developing new business, e-commerce and web applications.

4. Microkernel Architecture

There are software which have a certain set of operations that are used repeatedly in various patterns. The popular Eclipse development tool, for example, will open files, annotate them, edit them, and start background processors. 

The tool is famous for doing all this work with Java code and then when a button is pressed, compiling the code and running it.

What does it solve?

In this case, the basic routines for viewing a file and editing it are part of the microkernel. The Java compiler is just an additional part that screws in to support the basic functions of the microkernel. 

Other programmers have come up with the solution of extending Eclipse to develop codebase for other programming languages too.

Additional functions that overlap are often called add-ins. This extensible approach is also known as plug-architecture. 

The solution is to push some basic tasks, like asking for a name or verifying payment, in the microkernel. Different business units can write plugins for different types of declarations by joining the rules with calls to the basic functions in the kernel.

Warnings:

• Deciding what belongs to the microkernel is often an art. It should contain the code that is used frequently.

• Plugins should include a fair amount of handshake code so that the microkernel knows that the plugin is installed and ready to go.

• Modifying the microkernel can be very difficult or even impossible once multiple plugins depend on it. The only solution is to modify the plugins as well.

• Choosing the appropriate granularity for Kernel functions is quite difficult  to do in advance.

Better for:

• Tools used by a wide variety of people
• Applications which require a division between basic routines and higher degree rules

• Applications with a fixed set of basic routines and a dynamic set of rules that need to be updated frequently.

5. Space-based Architecture

Many websites are built around a database and they perform well as long as the database can keep up with the load. But when usage peaks and the database can't keep up with the constant challenge of writing a transaction log, the entire website crashes.

What does it solve?

The space-based architecture iavoids functional collapse under high load. The design was made by dividing processing and storage among different servers. 

The data is distributed among the nodes as well as the responsibility to answer the calls. 

Some architects have been using the term "cloud architecture" for this which is more amorphous. 

The name "space-based" refers to the "tuple space" of the users, which is cut to divide the work between the nodes.

Storing information in RAM makes many jobs much faster, and allocating storage with processing can simplify many basic tasks. But distributed architecture can make some types of analysis more complex. 

Calculations that need to be spread across the entire dataset, such as finding an average or performing statistical analysis, should be divided into subtasks, spread across all nodes, and then aggregated when done.

Warnings:

• Transactional support is quite complicated with RAM databases.

• Generating enough load to test the system can be challenging, but individual nodes can be tested independently.

• Developing the expertise to cache data to increase speed without damaging multiple copies is difficult.

Better for:

• High volume data such as click streams and user registrations

• Low-value data that can occasionally be lost without great consequence; in other words, not bank transactions.

• Social media apps

Conclusion:

With this we come towards the end of this comparison. I hope I was able to clear all your doubts regarding the different types of software architecture and which one is suitable for your business.

The next best step for you will be to choose the right software development company in India and get your enterprise app done by professionals. As you will agree, only an expert can come up with expert solutions.