Frameworks vs Programming Languages: What is the difference?

Learn the key differences between programming languages and frameworks for web, mobile, AI and cloud
Azumo Research
December 7, 2022
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Simply put, a programming language is a tool while a framework is a work platform. Stated another way, programming languages deal with syntax and semantics while software frameworks deal with architecture.

In layman's terms, a programming language helps you write code while a framework helps you design an application. Given this explanation, it's no wonder that so many people are confused about the two!

In order to clarify the distinctions between these two important elements of coding, let's take a closer look at each one.

Programming Languages

A programming language is what software developers use to create instructions for computers to execute. The instructions created in a programming language tell the computer or server what actions to take and how to take them. In order for these instructions to be executed, they must be translated into machine code, which is the only code that computers can understand.

Programming languages are classified by paradigms, which determine how the programmer writes the code. The most popular paradigms are object-oriented programming (OOP), procedural programming, and functional programming.

Object-oriented programming

OOP is a programming paradigm that uses objects and their associated procedures, or methods, to design and build applications. In OOP, each object is created to model some real-world entity, such as a person, place, or thing. Each object contains its own data and methods, which are used to manipulate that data.

The Basics of OOP

As mentioned above, OOP relies on objects to structure code. But what exactly is an object? In general terms, an object is a self-contained component that contains both data and procedures (or methods) for manipulating that data. An object can be thought of as a package that includes everything needed to perform a certain action or task.

How OOP Works

In OOP, data is organized into objects. An object is a collection of data and methods that act on that data. For example, an employee object might contain the employee's name, address, phone number, and salary. It would also contain methods for calculating the employee's pay and benefits.

Objects are created from templates called classes. A class is a blueprint for an object. It defines the behavior and properties of that object. For example, the employee class might specify that all employee objects must have a name, address, phone number, and salary. The class would also define the methods for calculating the employee's pay and benefits.

The advantage of OOP is that it makes code more modular and easier to understand and maintain. Since objects can be reused in different parts of a program or in different programs altogether, software developers can save time.

Four Basic Principles of OOP in Web Development

There are four basic principles of OOP: encapsulation, inheritance, polymorphism, and abstraction.

  • Encapsulation is the hiding of information so that it can only be accessed through the methods of the object.
  • Inheritance is the ability of one class to inherit the behavior of another class.
  • Polymorphism is the ability of an object to take on many forms dependent on how it is being used—for example, an employee object might behave differently when calculating pay than when calculating vacation time accrual.
  • Abstraction is the process of hiding information so that only the essential details are shown—for example, when you look at an employee object all you need to see is the employee's name rather than all the underlying code that makes up the object.

Applying these principles makes code more reliable because there are fewer opportunities for errors when code is well-organized into small modules that can be easily tested and updated as needed.

OOP has become increasingly popular in recent years due to its many benefits. For one, OOP allows for the modular construction of an application. This means that different parts of the code can be written and tested independently from one another before being integrated into the final product.

Additionally, OOP makes it easier to maintain and expand an application over time since new objects can be created and added as needed without disturbing the rest of the codebase. Finally, OOP facilitates code reuse through inheritance, which will be discussed in more detail below.

Despite these advantages, OOP is not without its drawbacks. One potential downside is that OOP can lead to more complex codebases since each object must be designed carefully and interacts with other objects in the system.

Additionally, OOP requires a good deal of upfront planning and design before any coding can begin. However, these disadvantages are often outweighed by the benefits of OOP for most applications.

OOP languages

  • Java
  • Python
  • C++
  • JavaScript
  • PHP
  • Ruby on Rails
  • Objective-C
  • Swift

Procedural programming

Procedural programming focuses on creating a list of instructions for the computer to execute. These instructions, or so-called "procedures," are typically organized into functions or subroutines.

How Procedural Programming Works

In procedural programming, the programmer writes a list of instructions for the computer to execute. These instructions are typically organized into functions or subroutines. Functions are usually self-contained units of code that carry out a specific task, while subroutines are smaller units of code that are called by functions to perform specific tasks.

Procedural programming languages typically use a top-down approach, meaning that the programmer starts with a general overview of the software application and then drills down to the details. This is in contrast to the software development process for OOP languages, which use a bottom-up approach in which the developer writing code starts with the details and then builds up to the general overview.

Advantages and Disadvantages of Procedural Programming

There are both advantages and disadvantages to using procedural programming. One advantage is that it can be easier for programmers to understand what a program is doing if it is written in a procedural language. This is because procedure-based programs tend to be more structured and linear in nature.

Another advantage of procedural programming is that it can be easier to debug programs written in these languages. This is because each function or subroutine can be tested individually before being integrated into the overall program.

However, there are also some disadvantages to using procedural programming languages. One major disadvantage is that these languages can be less flexible than other types of languages. This is because they often require all data to be passed through procedures, which can make it difficult to reuse code or add new features.

Another disadvantage of these languages is that they can be less efficient than other types of languages. This is because they often require more memory and processing power to run due to their need to store all data in procedures.

Procedural programing languages:

  • C
  • Fortran
  • Pascal
  • Basic

Functional programming

Functional programming is a programming paradigm that is based on the mathematical concept of a function. In functional programming, code is written as a series of self-contained functions that take input and produce output. This input and output can be data or other functions.

Functional programming is characterized by its focus on the evaluation of functions rather than on the side effects of commands or assignments. This allows for clearer and more concise code that is easier to reason about and debug. Additionally, functional programming languages are often easier to parallelize, which can lead to faster execution times.

Advantages of Functional Programming

There are several advantages of functional programming that make it well-suited for businesses:

  • Ease of reasoning: Functional programs are typically much shorter than programs written in other styles. This means there is less code to reason about, which makes it easier to find bugs and track down errors.
  • Greater clarity: Functional programming languages often have fewer special cases and side effects than imperative languages. This leads to code that is easier to read and understand.
  • Easier testing and debugging: Because functional programs are typically shorter and have fewer side effects, they are usually much easier to test and debug than programs written in other styles.
  • Faster execution times: Functional programs are often easier to parallelize than imperative programs, which can lead to faster execution times.
  • Better scalability: Many businesses choose functional programming because it makes it easy to scale their applications. With imperative languages, adding new features or scaling up an application often leads to a lot of messy code. However, with functional languages, such as Haskell or Ocaml, adding new features is much simpler and results in code that is more maintainable in the long run.
  • Better decision making: One of the most important benefits of functional programming is that it helps businesses make better decisions. By forcing programmers to think about the consequences of their actions before they write any code, functional programming can help businesses avoid costly mistakes.

Basically, functional programming is often used for data-intensive applications, as it can be more efficient to process data in this way.

Functional programing languages:

  • Haskell
  • OCaml
  • Lisp
  • Erlang
  • Clojure

Software Frameworks

A framework is a platform that helps coders design an application by providing pre-written code within templates.  A framework is a collection of library code that works together to simplify the syntax, grammar, or semantics of any language in which it is written.

This allows coders to save time by not having to start from scratch every time they want to create an application; they can simply fill in the blanks within the template according to their specific needs.

For example, if a developer wants to create an eCommerce website using PHP, they would likely use the Laravel framework because it has everything they need ready-made within its template—they would just need to add in the specifics related to their own website.

Web Application Frameworks

A web application framework is a software framework that is designed to simplify the development of web apps. This type of framework provides a structure for coders to follow, as well as pre-written code related to common tasks that are required in most web applications. Some popular web frameworks for web application development include: Ruby on Rails, Django, Node, React, Flutter and Laravel.

Ruby on Rails: Ruby on Rails is a framework written in the Ruby programming language. It is designed to make the development of web apps much simpler by providing a structure for coders to follow, as well as pre-written code related to common tasks that are required in most web apps.

Django: Django allows for the creation of powerful and dynamic websites. Written in Python, Django makes use of the language's flexibility to quickly create complex code structures. In addition, Django includes a number of built-in features that make it easy to create robust and secure web applications.

Flask: Flask is a micro web framework written in Python. It is classified as a micro-framework because it does not require particular tools or libraries. It has no database abstraction layer, form validation, or any other components where pre-existing third-party libraries provide common functions. However, Flask supports extensions that can add application features as if they were implemented in Flask itself. Extensions exist for object-relational mappers, form validation, upload handling, various open authentication technologies and several common framework related tools. Extensions are updated far more regularly than the core Flask program. Flask is commonly used with MongoDB, which gives it more control over databases.

Laravel:  This is a PHP framework. It is free and open source. It was created by Taylor Otwell. It follows the model-view-controller (MVC) architectural pattern. Laravel aims to make web development simple, easy and fast by providing expressive syntax and conventions over configuration.

React: React is a declarative, efficient, and flexible JavaScript library for building user interfaces for web and mobile. It lets you compose complex UIs from small and isolated pieces of code called “components”. React has been designed from the start for gradual adoption, and you can use as little or as much React as you need. React can be used as the front-end web development tool for various programming languages.

Node: Node.js is a JavaScript runtime built on Chrome's V8 JavaScript engine. It is designed to make the development of web apps much simpler by providing a structure for coders to follow, as well as pre-written code related to common tasks that are required in most web apps. It is considered a server side technology, as opposed to a client side technology like JavaScript.

Nest.js: Nest.js is a modern framework for building efficient, scalable Node.js server-side applications. It uses progressive JavaScript, is built with TypeScript (that supports JS), and combines elements of both OOP and Functional Programming. Nest.js is also easy to use and learn, it has a very small learning curve and is suitable for both beginners and experienced developers.

Mobile Application Development Frameworks

Cross platform applications benefit immensely from the use of frameworks. Similar to a web application framework, mobile framework are designed to simplify the development of mobile apps.  These types of software frameworks provide a structure for software development across mobile platforms.  Developers can have pre-written code related to common tasks that are required in most mobile apps. There are many different frameworks. Some popular frameworks for mobile application development include: React Native, Ionic and Flutter.

React Native: React Native is a JavaScript framework for writing real, natively rendering mobile apps for iOS and Android. It’s created by Facebook and used by such companies as Instagram, Airbnb, Tesla, and Walmart.

Ionic: Ionic is an open source framework used for developing mobile applications. It is a cross-platform framework, which can be used to develop applications that can be run on both Android and iOS platforms.

Flutter: Flutter is a cross-platform mobile application development framework written in Dart, created by Google. It allows developers to write code that works on both iOS and Android devices. You can find our blog post on why we like Flutter here.

Xamarin: Xamarin is a cross-platform mobile application development tool that can be used to develop applications for Android, iOS applications and Windows platforms. It uses the C# programming language and the .NET framework.

Popular Frameworks for Machine Learning and Data Science

There are many different machine learning software frameworks out there, each with its own advantages and disadvantages. In this section, we'll take a look at some of the most popular ones.

TensorFlow is one of the most popular AI frameworks available today. It was developed by Google and is used in many of their products, such as Google Translate a natural language processing framework that leverage BERT. Ultimately it enables language modeling and is used in conversation apps and chatbots.

BERT is a deep learning framework that helps developers create sophisticated natural language processing models. BERT is designed to enable developers to create applications that can understand human language. The framework is based on the Transformer model, which was developed by Google AI researchers. Facebook a flavor called RoBERTa.

Keras is another popular framework. It was developed by the creators of TensorFlow, and it's designed to be simple and easy to use. Keras can be used for a variety of tasks, including: image classification, object detection, Pose estimation, text recognition, and more.

scikit-learn is a framework that is popular in the Python community. It's designed to be easy to use and efficient. Scikit-learn is used for a variety of tasks, including classification, regression, and clustering.

Theano is another ML framework that is popular in the Python community. It was developed by the creators of TensorFlow. Theano is a deep learning library that allows you to define, optimize, and evaluate mathematical expressions involving multi-dimensional arrays efficiently.

Pytorch is a framework that is popular in the artificial intelligence community. It's developed by Facebook AI Research. Pytorch is often used for deep learning applications. Some popular applications that use Pytorch include: NLP, Computer Vision, Time Series Prediction, and Recommendation Systems.

OpenCV is one of the most popular computer vision frameworks available today. It was developed by Intel and is used in many products, such as the Nest Cam. It can also be used for image recognition.

These AI and datascience frameworks are popular because they're open source, easy to use, and have a large community of users.

DevOPs Frameworks

There are several such frameworks available to help organizations implement DevOps practices, many of which are open source. Some popular DevOps frameworks include:

  • Puppet
  • Chef
  • Ansible
  • SaltStack
  • Vagrant
  • Docker
  • Kubernetes

These third party tools and frameworks have many strengths and weaknesses, so it's important to choose the right one for your organization's needs. In short they enable micro-services, allow you rapidly deploy ML powered applications and do large scale data processing or manage massive cloud environments. Services like Puppet essentially serve as a code library for managing the production deployment of services.

Apache Spark

Apache Spark is a general purpose cluster computing platform. It provides high-level APIs in Java, Scala, Python and R, and an optimized engine that supports general execution graphs. It also supports a rich set of higher-level tools including Spark SQL for SQL and structured data processing, MLlib for machine learning, GraphX for graph processing, and Spark Streaming.

Spark has been designed to run on a wide variety of hardware, including commodity hardware as well as more specialized systems such as GPUs and FPGAs. It can also be deployed in a variety of ways, including on-premises, in the cloud, or via a managed service.

There is no one-size-fits-all answer to whether it is a framework, as the best framework for Apache Spark depends on the specific needs of your organization. However, some of the most popular options include Databricks, Hadoop, and Flink.

Spark has a number of features that make it well suited for large-scale data processing:

  • It is easy to use and can be integrated with a wide variety of programming languages.
  • It has a powerful execution engine that supports multiple types of data processing including batch, interactive, and stream processing.
  • It supports a wide range of data formats including structured, semi-structured, and unstructured data.
  • It can be deployed in a variety of ways including on-premises, in the cloud, or via a managed service.

While an object oriented programming language, some consider Java as both a language and a framework, in that it is one that can be used to communicate and also to provide a structure for something. An example of such a technology is the Java programming language. Java can be used to write programs that run on a computer, and it can also be used to create websites. The Java language provides a framework that makes it easy to create websites that are interactive and look professional.

Computer programming is complex. This post offered just a few examples of programming languages and frameworks used in developing software.  There are many other frameworks. While both programming languages and frameworks are necessary for creating software applications, it's important to understand the key differences between them in order to use them effectively.

Programming languages provide the building blocks for software applications while frameworks provide templates with pre-written code that save time and reduce errors for coders who are designing an application from scratch.

Being aware of these distinctions is sure to help you streamline your decisions and create better software faster.

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