Reactive vs Imperative Programming

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A few years ago Reactive Programming was introduced as an improvement upon the imperative programming paradigm. It provides some important advantages over the imperative way by relying on asynchronous programming. These days we see a lot of enterprise applications use the reactive way but still, there are ones using the imperative approach. In this blog, we will try to explore what are the differences between reactive and imperative programming what are their use cases and what are the advantages/disadvantages of these programming paradigms.

Imperative Paradigm

Imperative programming is a software development paradigm that focuses on on solving a problem by performing a sequence of steps. In imperative programming, the code specifies how the problem is to be solved by executing steps that change the program’s state. For example, assigning values to variables, controlling the flow of execution with loops and conditionals, and calling functions to perform specific tasks. Imperative programming focuses on describing how a program should work to solve a problem or acheive a desired result.

  1. Easy to Learn: Imperative programming is basically the way we think in real world about how to solve our problems hence it is usually easier to learn for beginners than other programming paradigms, as we are a;ready used to solving problems in this way.
  2. Precise Control: Imperative programming allows for precise control over the flow of a program which is essential for systems which require very high efficiency.
  3. Efficiency: Imperative programming languages are good for compute intensive tasks as they can be highly optimized which allows the system to acheive high performance.
  4. Low-level Programming: Imperative programming is mostly used in low-level programming, like kernels or device drivers, because it provides provides high level of control over the hardware. Communication between hardware and drivers can be highly optimized with the help of these languages.
  1. Limited Abstraction: It is difficult to acheive abstraction in imperative programming. This makes it difficult to design larger complex system as it’s availability is highly compromized due to limited abstraction of errors/issues.
  2. Prone to Errors: The close relationship between program flow and program state makes it more prone to errors and bugs in larger complex systems
  3. More Code: Imperative programming usually requires a lot more lines of code than other paradigms, which leads to very high amounts of boilerplate code that can be difficult to manage in large complex systems.
  4. Difficult to Parallelize: Imperative programming is difficult to parallelize, which is highly disadvantageous for distributed systems as it compromises on concurrency.

Reactive Paradigm

Reactive programming is a programming paradigm that focuses on the flow of data and how it changes over time. It is based on event-driven programming concept where data streams get processed asynchronously i.e. when they arrive. ReactiveX is a software library that aims to provide reactive programming concept to various programming languages. It provides the advantages of the Observer pattern, the Iterator pattern, and functional programming. There are libraries from different languages based on ReactiveX such as RxJava, RxJS, Rx.NET, RxScala, etc.

Properties of Reactive systems

According to The Reactive Manifesto, a reactive system is designed to be:

Responsive:  Responsive systems focus on providing rapid and consistent response times. This consistent behavior builds end user confidence and encourages further interaction.

Resilient: Failures are contained within each component, isolating components from each other and thereby ensuring that parts of the system can fail and recover without compromising the system as a whole. This ensures high availability of the system.

Elastic: Reactive Systems stay responsive and can react to changes in the input rate by increasing or decreasing the resources allocated to service these inputs. This feature helps in high scalability.

Message/Event Driven: Reactive Systems rely on asynchronous message-passing to establish a boundary between components that ensures loose coupling, isolation, and location transparency. Non-blocking communication allows recipients to only consume resources when actively triggered(by a call/message/event). This ensures less system overhead and in-turn better performance.


Reactive programming has some potential disadvantages that developers need to consider when using it. Here are some of them:

  1. Steep Learning Curve: Reactive programming involves a fundamentally different way of thinking about programming than traditional imperative programming. It requires developers to think about streams of data and how to react to them in real time.
  2. Debugging and Testing Complexity: As events are processed asynchronously, it can be challenging to trace the sequence of events that led to a problem. Moreover, the complex interactions between events, subscribers, and publishers can make it difficult to write comprehensive test cases.
  3. Performance Overhead: Reactive programming can introduce some performance overhead due to the need to manage and coordinate streams of data which is most noticeable in applications that involve a high volume of data or a large number of subscribers.
  4. Complex Data Flow: In reactive programming, data flows can become quite complex, especially as applications become larger and more complex. This can make it difficult to reason about the behavior of the system and maintain it over time.
  5. Resource Consumption: Reactive programming can consume a significant amount of resources, especially in applications that process a large number of events or that require real-time responsiveness.

Use Cases

Imperative: This programming paradigm is useful when you want to perform a series of tasks in a specific order, and when you need to control the exact flow of data and control structures. Imperative programming is used in procedural languages like C, Python, and Ruby.

Reactive: This programming paradigm is useful when you need to deal with large streams of data that are constantly changing, such as data from sensors or user inputs. Reactive programmingis used when you need to react to changes in real time. Reactive programming is used in languages like Java, JavaScript, and Scala.


In this blog we learned the imperative and reactive way of programming and when to use them as well as their differences in approach. For more such informative tech blogs keep following Knoldus Blogs.

Written by 

Agnibhas Chattopadhyay is a Software Consultant at Knoldus Inc. He is very passionate about Technology and Basketball. Experienced in languages like C, C++, Java, Python and frameworks like Spring/Springboot, Apache Kafka and CI/CD tools like Jenkins, Docker. He loves sharing knowledge by writing easy to understand tech blogs.