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Table of contents
Data Structure And Algorithm:
Importance of Data Structure:
Programming Language to start your Career:
Java Or Python : Which one is for you?
Languages to learn
Top Programming Language For Competitive Programming
Features of Python:
Features of Java:
Features of C++:
Features of C:
Features of C#:
Features of JavaScript:
Features of Ruby:
Data Structure in day to day life:
Using Queue Data Structure as Boarding a Bus:
Using Graph Data Structure For Google Maps and Social Media:
Using Stack Data Structure For Pile of Plates:
Learning Multiple Programming Languages:
Best Courses to learn Data Structure and Algorithm:
Frequently Asked Questions
Which programming language is best for data structures and algorithms?
Are data structures and algorithms the same for all languages?
What are the top 10 programming languages?
Can I learn data structures and algorithms in Python?
Is Google written in Python?
Should I learn Java or Python?
How do I start learning DS and algorithms?
Which language is best for DS and Algo?
How do I prepare for DS and algorithms?
How long will it take to learn data structures and algorithms?
Is Python good for Data Structures?
Is Python good for algorithms?
Last Updated: Apr 2, 2024

Programming Languages with Data Structures

Author Ravi Khorwal
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Programming languages are a type of computer language that is used to implement algorithms on computers. One of the most challenging questions in today’s world that we all face is which programming language should be chosen for learning Data Structures and Algorithms? 

Programming languages and data structures

Let’s take a look at the most widely used programming languages for learning Data Structures and algorithms:

  • Java – When it comes to server-side application development, Java is the undisputed king. It’s a class-based, object-oriented programming language used to create software, mobile apps, web apps, games, web servers, and application servers. Java has long been the most popular programming language for Android app development.
  • Python – Python is extremely popular among programmers and data scientists due to its ease of use and adaptability. Python is a beginner-friendly language with a simple learning curve and English-like syntax. Python also provides library support for a wide variety of development needs.
  • C++ – C++ is a cross-platform, general-purpose programming language. It combines the advantages of object-oriented programming, imperative programming, and generic programming languages. It gives programmers complete control over memory and system resources. The two main characteristics of C++ are speed and efficiency, which is also why it is widely used for doing competitive programming.
  • C – C is a highly portable programming language widely used in Windows, UNIX, and Linux operating systems for scripting system programmes. C is a general-purpose programming language that may be used to create corporate programmes, games, graphics, and computations, among other things.

And there is a long list for this. Now, should we learn all of the programming languages? The answer is No, you need not.

Learning one language is sufficient to start a career as a software developer. Once you learn one programming language in-depth, then you can learn the other programming languages easily.

But in order to learn a programming language, you should know each in and out of the concepts, fundamentals used in the programming language.

Also see, Must Do Coding Questions

Data Structure And Algorithm:

Data Structure and Algorithm contains two terms:

  • Data Structure
  • Algorithm

Data Structure refers to the storage, arrangement, and organization of the data. And this algorithm is basically solving a problem step by step. To solve a problem step by step by arranging the data in an efficient manner.

Data Structure refers to the storage, arrangement, and organization of the data. And this algorithm is used for solving a problem step by step by efficiently arranging the data. In short,  data structures and algorithms are all about writing optimized codes.

In other words, it would be right to say that data structure is the organization of data that enables us to perform some of the operations in an efficient manner.

An algorithm helps us to solve the same problem in milliseconds while other algorithms would take a much longer time to do so.

Recommended Topic, Cognizant Eligibility Criteria, hash function in data structure.

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Importance of Data Structure:

Let’s talk about how important a Data structure and algorithm is and what role it plays in a programming language? Storing as well as arranging the data in the disk space of the computer or memory storages the system is the data structure.

Now, why is this done? This is done because if data is stored in an efficient manner, then they can be retrieved and accessed easily, which will increase the performance.

Are these things really needed in real life?

Let’s understand with the help of an example.

Let’s say you have a book of 70000 pages, in which your roll no. is there.

Now, suppose you need to search your roll number. How will you actually do that?

There could be a number of ways to search the roll no in that 70,000 pages book, but we need to find the most efficient method out of them.

  • You will start searching from the very beginning and will keep on finding it. But in this way, it will take too much time to find your roll no, if let’s say is on page 67000.
  • To avoid this, you may use a Binary Search to find your roll number.

In this, you would go to page no. 35,000 and will see your roll no on that page, now if all the roll no. on the page are lesser than your roll no then you will go to page no. 35000+(35000/2).

By continuing this way, you would be able to find the roll no. in a much shorter span of time. This is one of the most efficient ways of searching.

Recommended Topic About, 8085 Microprocessor Pin Diagram and Ensemble Learning

Programming Language to start your Career:

It never matters how many languages you have gone through. The thing that matters is how much have you gone through in that language.

Better to know the concepts thoroughly used in the language than learning multiple languages. To start the career as a software developer, a person can pick any language like Java, C++, Python, Node.js etc. and can start his/her career.

The language must be Object-Oriented language. The reason behind picking Object Oriented language is that you can learn any other language easily.

It is very important to learn the fundamentals of the programming language thoroughly as these are things that can make a strong base of yours.

People who have sound knowledge of the fundamentals of data structures and algorithms are better programmers than others and are paid much higher.

Most of the technical interview focuses primarily on data structure and algorithm skills only. This is so because those who have good knowledge of Data Structure and Algorithm are good problem solvers and have logical minds.

Software developers are paid higher than people in different sectors and this is because they solve complex real-world problems because of their strong coding skills which ultimately is because of their strong Data Structure And Coding Skills.

They keep on solving problems which people think cannot be solved.

During my final year days, I used to apply for different Software Engineer positions, at that time I could find one common thing among those interviews, which was the Data Structure and Algorithm part.

More than 98% of companies search for the candidate who has sound knowledge of data structure and algorithms and this decides your pay as well.

You can check out 7 Tips to improve logic for programming.

Java Or Python : Which one is for you?

People often confuse the language to choose to start a career with as a software developer. Well, Java is a language that would never fade away and many big giants use java and would keep using it.

On the other hand, Python is the future and its development would be helpful in many areas without a doubt. Python somehow is more productive than Java. Writing code in Python is much easier and it provides rapid development of many of the applications.

One of the reasons behind so much the popularity of this language is that code is quite simpler and much easier to write and the length of the code is also quite short.

It is also better to learn the data structure and algorithm in the same language which you have chosen as your primary language.

Languages to learn

In the field of programming, there are about 700 programming languages.

Understanding the importance of each programming language and how it affects the tasks we need to complete is critical.

Since we won’t be able to look at all 700 of these coding languages altogether, it’s a good idea to go through some of the most popular languages in 2021 and beyond.



Future Scope

1.PythonPython, without a doubt, has a bright future in the programming language development area, particularly in the disciplines of data visualisation, artificial intelligence, Data Science and machine learning.
2.JavaJava is widely utilised in many businesses. It may also be used to make a variety of goods and has a wide range of uses. It is currently the most widely used programming language, so it’s pretty worth learning.
3.C++C++ has a wide range of applications, and studying it is never a bad thing. It is a very simple language to pick up and understand. In the industry, it has a wide range of applications. Along with graphic designs and 3-D models, it’s also employed in games.
4.CAlthough C is out of date in some applications, it is not going away anytime soon. It has a wide range of real-world applications, and it will continue to be used in the industry for many years to come. 
5.C#C# is a language that is gaining in popularity and is likely to remain so in the coming years due to its effective capabilities in producing games and its resilience, both of which benefit the gaming industry. It’s also quite beneficial in business applications.
6.JavascriptJavaScript is a widely-used programming language. It is so extensively used that another programming language may take a long time to replace it. It is also used in artificial intelligence and other fields, in addition to web development. This language should be at the top of anyone’s learning priority list.
7.RubyIn today’s world, Ruby is still utilised for a large number of applications. As a result, it’s a great language to learn because you’ll be able to create complex apps in no time. It also has robust technology. Therefore it is still relevant today.

Check this out:  R Programming language

Top Programming Language For Competitive Programming


Python is a popular choice for competitive programming due to its simplicity, readability, and vast library support. It offers concise syntax, making it easy to write and understand algorithms quickly. Python's dynamic typing and high-level data structures allow programmers to focus more on problem-solving rather than low-level details.

Features of Python:

  1. Readability: Python's clean and readable syntax reduces the time needed to write and debug code.
  2. Interpreted: Python's interpreted nature eliminates the need for compilation, allowing for faster development and testing.
  3. Vast Library Support: Python comes with a rich standard library and numerous third-party libraries for tasks like data manipulation, mathematical computation, and algorithm implementation.
  4. Dynamic Typing: Python's dynamic typing feature allows variables to be reassigned with different data types, providing flexibility in programming.
  5. High-Level Data Structures: Python provides built-in support for high-level data structures like lists, dictionaries, and sets, simplifying complex data manipulation tasks.


Java is another popular language for competitive programming, known for its platform independence, strong type system, and extensive standard library. Although Java's syntax may be more verbose compared to Python, it offers robust features and performance.

Features of Java:

  1. Platform Independence: Java programs can run on any platform with the Java Virtual Machine (JVM), making it suitable for cross-platform development.
  2. Strong Type System: Java's static typing ensures type safety at compile time, reducing runtime errors and enhancing code reliability.
  3. Large Standard Library: Java's extensive standard library provides ready-to-use classes and utilities for various programming tasks, including data structures and input/output operations.
  4. Object-Oriented: Java's object-oriented programming paradigm encourages code reusability, modularity, and scalability through encapsulation, inheritance, and polymorphism.
  5. Memory Management: Java's automatic memory management system, including garbage collection, simplifies memory allocation and deallocation, reducing the risk of memory leaks and memory-related bugs.


C++ combines high-level features with low-level control, making it a powerful language for competitive programming. It offers performance optimization, efficient memory management, and a rich set of features for algorithm implementation.

Features of C++:

  1. Performance: C++ allows fine-grained control over memory allocation and CPU utilization, enabling programmers to write high-performance code.
  2. Standard Template Library (STL): C++ provides a comprehensive standard library that includes containers, algorithms, and utilities, simplifying complex data manipulation and algorithm implementation.
  3. Object-Oriented: C++ supports object-oriented programming concepts like classes, inheritance, and polymorphism, facilitating code organization and reuse.
  4. Low-Level Manipulation: C++ allows direct memory manipulation and provides features like pointers and references, enabling efficient implementation of algorithms and data structures.
  5. Compiler Optimization: C++ compilers perform extensive optimization during compilation, resulting in highly optimized executable code with minimal runtime overhead.


C is a widely used programming language known for its simplicity, efficiency, and portability. It offers low-level control over system resources and is often preferred for system programming and embedded systems development.

Features of C:

  1. Efficiency: C's simple syntax and minimal runtime overhead make it an efficient choice for programming tasks that require direct access to hardware resources or high performance.
  2. Portability: C programs can be easily ported across different platforms and architectures with minimal modifications, making it suitable for cross-platform development.
  3. Close-to-Hardware: C allows direct manipulation of hardware resources through features like pointers and memory management, making it ideal for system programming and embedded systems development.
  4. Standard Library: C provides a compact standard library with essential functions for input/output operations, string manipulation, and mathematical computations, ensuring portability and compatibility across systems.
  5. Procedural Programming: C follows a procedural programming paradigm, focusing on functions and procedures, which simplifies code organization and promotes reusability.


C# is a modern programming language developed by Microsoft, primarily used for building Windows applications, web applications, and games using the .NET framework. It combines the power of C++ with the simplicity of languages like Java and Python.

Features of C#:

  1. Integrated Development Environment (IDE): C# is tightly integrated with Microsoft Visual Studio, providing a powerful IDE with advanced debugging, profiling, and code analysis tools.
  2. Object-Oriented: C# supports object-oriented programming concepts like classes, inheritance, and polymorphism, promoting code organization, modularity, and reusability.
  3. Automatic Memory Management: C# features automatic memory management through garbage collection, simplifying memory allocation and deallocation and reducing the risk of memory leaks.
  4. Language Interoperability: C# is designed to interoperate seamlessly with other languages in the .NET ecosystem, allowing developers to leverage existing libraries and components written in different languages.
  5. Rich Standard Library: C# provides a comprehensive standard library with built-in support for common programming tasks like input/output operations, networking, and database access, enhancing developer productivity and code quality.


JavaScript is a versatile programming language commonly used for web development, including client-side scripting, server-side scripting, and building web applications. It offers dynamic typing, event-driven programming, and asynchronous programming features.

Features of JavaScript:

  1. Client-Side Scripting: JavaScript is primarily used for client-side scripting in web browsers, enabling dynamic interactions and user interface enhancements.
  2. Event-Driven Programming: JavaScript supports event-driven programming paradigms, allowing developers to respond to user actions and browser events efficiently.
  3. Asynchronous Programming: JavaScript features asynchronous programming patterns like callbacks, promises, and async/await, facilitating non-blocking I/O operations and improving application responsiveness.
  4. Cross-Platform Compatibility: JavaScript code can run on various platforms and devices with web browser support, making it suitable for building cross-platform web applications.
  5. Extensive Ecosystem: JavaScript has a vast ecosystem of libraries, frameworks, and tools like Node.js, React, and AngularJS, enabling developers to build complex and scalable web applications with ease.


Ruby is a dynamic, reflective, object-oriented programming language known for its simplicity, expressiveness, and developer-friendly syntax. It emphasizes productivity and developer happiness, making it popular for web development and prototyping.

Features of Ruby:

  1. Expressive Syntax: Ruby features a clean and expressive syntax with natural language constructs, making it easy to read, write, and understand code.
  2. Object-Oriented: Ruby is a pure object-oriented language, where everything is an object, including primitive data types and functions.
  3. Dynamic Typing: Ruby employs dynamic typing, allowing variables to hold values of any type and enabling flexible and concise code.
  4. Metaprogramming: Ruby supports metaprogramming techniques like reflection and method_missing, empowering developers to write expressive and flexible code.
  5. Rich Standard Library: Ruby comes with a rich standard library and a vibrant ecosystem of gems (packages) for various programming tasks, including web development, testing, and data manipulation.

Data Structure in day to day life:

Why are we learning Data Structure?

Do we really encounter all these in our daily lives?

There are multiple scenarios where we need these data structures and algorithms in our lives.

Some of them are:

Also read - Data Structure MCQ

Using Queue Data Structure as Boarding a Bus:

A queue is a data structure that is of linear type. In Queue, elements are arranged in the First In First Out manner which is abbreviated as FIFO.

Suppose, there are 10 passengers standing in a row to board the bus. The passenger who comes first would get boarded first on the bus.

This is shown through the picture shown below. Whenever there is a new passenger, it can come through the backside only which means he/she can board the bus in the last only.

Let’s understand it with the help of commands given to the printer.

Suppose there is a small organization, which has only one printer, and let’s say five commands are given to the printer to print the doc.

So, all 5 commands will be stored in the queue and they will be printed in FIFO order only. That means the second command will be printed only once the first command is executed.

You can also read about mock interview.

Using Graph Data Structure For Google Maps and Social Media:

Google Map is one of the widely used and useful technologies developed by Google. According to Wikipedia, in 2020, over 1 billion people used google maps per month.

This google map uses Graph as the data Structure to predict the paths and the traffics shown over there.

Using Graph Data Structure For Google Maps and Social Media

A graph is considered to be an interconnected item and each item is basically a node and distance between two nodes is an edge. Social Media is also an example of a Graph data structure.

We use Facebook, Instagram, Tinder etc. All these social media use graphs. Every user on these social media can be considered as the node and when we connect through the node it is called edge.

The more we connect with people, the more edges will be there and eventually, it will form a network something like Facebook we use.

Using Stack Data Structure For Pile of Plates:

A stack is the Data Structure which is used and can be related to the piles of plates that we often see in our kitchens, in marriage functions etc. These follow the Last In First Out approach (LIFO).

It can be visualized how plates are put on over the other and the plate which we put at the last is the one which gets out first. Insertion and removal can be done from the top only.

Now, we talked about how a data structure and algorithm is useful and powerful in the programming field and in the day to day life as well.

Now, let’s talk about why 1 language is more than enough to start a career in the software development field.

Learning Multiple Programming Languages:

Well, there is no harm in learning multiple programming languages. But do not prefer this over Data Structure and Algorithm. Never do so.

Always pick one OOP language, try to grasp all the concepts of the language. Pick the data structure and algorithm with the same language.

Now, you may learn as many languages as you wish.

You may pick the languages there in the market. It is always important to focus on DSA, chances will be increased to get hired as a software developer in FANG companies if you acquire good DSA skills, but yes languages will be cherished.

Must Read Algorithm Types

Best Courses to learn Data Structure and Algorithm:

There could be plenty of courses in today’s digital era. But choosing the one wisely which is worth spending money and time is really important.

Let’s discuss some of the best courses available:

  1. Data Structure and Algorithm by Coding Ninjas:
    Coding Ninjas offers one of the most complete courses of Data Structures and Algorithms in terms of content, money and learning, mentorship. I myself took the course of coding ninjas which is Data Structure and Algorithm in Java and found it really helpful. Hence, these are really nice courses.
  2. Learning data Structure and Algorithm in Python from Scratch:
    The course can be accessed through Udemy easily. To start a course in Python from scratch, you may go for this course. As already discussed Python is going to dominate over the tech world for the next decade for sure.
  3. From 0 to 1: Data Structure and Algorithm in Java:
    This course is delivered by some of the most experienced people from big company including Facebook, Microsoft, and Amazon. This course will take you from negative to industry-ready. Visualization is very important to understand good levels of data structure and algorithms.

Learning just one programming language is more than sufficient if you master data structure and algorithm skills enough to solve real-world problems.

Must Read Julia Programming Language.

Get detailed information about FAANG companies here.

Read about Application of Queue in Data Structure here.

Check this out:  R Programming language

Frequently Asked Questions

Which programming language is best for data structures and algorithms?

Data structures and algorithms are not language specific and hence you can use any language be it JavaScript, C, C++, Java or Python. You should feel comfortable with the syntax of the language and you are good to go.

Are data structures and algorithms the same for all languages?

Yes, the concepts for data structures and algorithms are same for all languages. The only thing that changes is the syntax.

What are the top 10 programming languages?

The top 10 programming languages include Python, JavaScript, Java, C#, C, C++, GO, R, Swift and PHP.

Can I learn data structures and algorithms in Python?

Yes, you can learn data structures and algorithms in Python.

Is Google written in Python?

Python is one of the official languages of Google in addition to other popular languages such as C++.

Should I learn Java or Python?

It depends on your use case. If you wish to go for competitive programming, pick Java. If you wish to go for development, learn Python.

How do I start learning DS and algorithms?

After mastering one programming language, the next step is to use that language to implement data structures. Starting from linear data structures, move towards advanced topics but don’t just study topics theoretically. Simultaneous implementation is important. To get a defined path, taking an online course is recommended.

Which language is best for DS and Algo?

Most competitive programmers use C++ because of its efficiency for DSA. That being said, the language is just a medium and any language that you are affluent with is appropriate for you to implement DSA.

How do I prepare for DS and algorithms?

Practicing as many problems as you can find and that too consistently is the key to mastering DSA. Online platforms like Coding Ninjas Studio, LeetCode, Codeforces have a pool of problems of all types, practicing which will help you master DSA.

How long will it take to learn data structures and algorithms?

On a generic note, mastering DSA will take around 3-4 months. A good foundation is important so do not rush through it, be patient and take your time because the pace of learning is different for every learner.

Is Python good for Data Structures?

Python is considered to be a good language to start with if you are a beginner. Moreover, in terms of speed, there is no better language than Python. In the aspects of speed, convenience and syntax, python is a good language for Data Structures.

Is Python good for algorithms?

Algorithms are not written with the medium of programming languages. They are essentially written in a syntax which is considered to be the closest to Python due to Python’s closeness to the English language.


We discussed how important data structure and algorithms are to solve real-world problems and how effectively it is being used worldwide. But on the other hand, knowing more than one language is not a bad thing either.

If you have mastered data structure and algorithm skills good enough then definitely you may choose to learn some other language. You should keep yourself updated with the latest market trend definitely. For example: If you are a tech guy then according to the latest market trend you must know what Machine learning and Artificial Intelligence is.

To learn more about Data Structures and Algorithms, you can enroll in our DSA in C++ Course.

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