Node.js Vs JAVA Vs Python- How to Choose the Best Backend Tech Stack?
Node.js Vs JAVA Vs Python- The Better Way to Build Backend in 2021
Looking for the best backend technology stack? Confused between Node.js Vs. Java Vs. Python? No worries! Get into this detailed comparison and pick the right one for your project.
Python, Java, and Node.js are popular backend choices. They empower globally successful brands like Google, Wikipedia, Netflix, LinkedIn, even NASA. All three enjoy a prominent market status, millions of developers, and billions worth of project development.
So, when a developer sits down to choose the backend programming language for their project, how can they decide which is better?
Node.js, Python, and Java are locked in a battle for control as obvious forerunners in the field. The Internet is swarming with comparative information over NodeJS Vs. Python, NodeJS Vs. Java, or Python Vs. Java. But, as a developer, I believe the questions about this subject have evolved. Now, there is no absolute answer, rather a circumstantial choice.
For instance, if I were working on choosing a backend, here’s what I would want to know.
- Which, amidst Java, Python, and NodeJS, is effective for my project’s backend?
- Is it fair to expect one of them to win, to be the best?
That is the mind frame with which we’ll work out an optimized way to choose the best backend technology stack between Node.JS, Java, and Python.
Let’s work on getting those answers, shall we?
Brief Introductions to Java, Node.js, and Python
Before we get into the nitty-gritty of Node.js Vs. Java Vs. Python, take a quick look at what each of these is.
What Is Java?
Java is a high-level, fundamentally object-oriented language. It’s been in action since 1995 and sustained itself as a top development choice for most of those twenty-six years. Furthermore, it has always changed course with the market and resolved its weaknesses through extensive innovation and feedback incorporation over the years.
What Is Python?
Python is a thirty-year-old, interpreted, high-level scripting language. It is implemented as a scripting language for web applications and is known for its code readability. Over the years, it has remained the only language with a consistent position amidst the ten best backend technology stacks. It’s currently used by leading organizations like Google, CERN, NASA, Facebook, Amazon, Instagram, Spotify, ITA, Yahoo, etc.
What Is Node.js?
When compared to Python and Java, Node.JS is a relative newcomer. Yet, despite its initial release in 2009, it keeps rising as one of the best open-source backend runtime environments. As of now, it powers globally prominent enterprises like Microsoft, GoDaddy, IBM, LinkedIn, Netflix, Rakuten, PayPal, Walmart, and many more.
Node.js Vs. Python Vs. Java- A Comparative Overview
Take a look at three of the best backend technology stack known to present-day developers. Compare them using these critical standards and choose the ideal resource for your project.
1. Java Vs. Node.js Vs. Python: Speed
Between the three, modern Java almost always provides a higher, more optimized speed. In fact, it can be ten times faster than Python or PHP. The reasons-
Effective native code compiler Thread-based memory sharing Just-in-time compilation Extensively developed Java Virtual Machine Statistically typed language Byte code precompilation
Of course, realizing this potential heavily depends on how you use Java. There are instances where Java can fall short on speed. Although, mismatched use cases, legacy code, and developers are to blame in most cases.
Node.js is a wonderful alternative to Java in instances where the latter fails to generate enough speed.
Moreover, between Node.js Vs. Python, the former wins in speed. Node.js is one of the fastest server-side solutions. The V8 engine interprets the JavaScript code into machine language and optimizes the solution to reduce loading time. Also, it follows an event-driven architecture. The resultant asynchronous calls facilitate better concurrent request processing by limiting memory issues.
That is why, despite being single-threaded, Node.js is faster than Python.
2. Java Vs. Node.js Vs. Python: Performance
Before considering Java Vs. Node.js Vs. Python performance standards, understand the connection between use cases and performance constraints.
While one of these backend languages may suit real-time solutions and mission-critical applications, another might serve large-scale projects better. Therefore, it is critical to truly understand what you want to achieve before choosing the best backend technology stack for that purpose.
Java has inbuilt multi-threading. Node.js has the V8. And Python, well, performance is not its best aspect.
And yet, if you are creating a solution that does not have to be ultra-fast, you can choose Python. As long as your customers and end-users can work on the solution without experiencing any significant slowdown, whichever backend language you select would be acceptable.
Having said that, if you want to know more about exact performance metrics for Node.js Vs. Java Vs. Python, check out this Computer Language Benchmark Game.
3. Java Vs. Node.js Vs. Python: Scalability
When determining scalability, ask this of any language- Is there an opening to bypass its performance limitations through additional resources?
The answer will vary depending on the language as well as your development requirements.
Node.js is quite scalable, owing to microservices, event-driven architecture, and non-blocking I/O. It allows the creation of microservices and modules. Whenever the solution expands, these microservices and modules resort to dynamic process runs and keep the performance and speed in check.
Java provides a good range of scaling opportunities.
Java uses an automatic garbage collector for memory management. It prevents the programmers from stressing about manual memory management and helps us avoid memory leaks. Combined with an optimized ecosystem, this module makes Java a decent choice for scalable web development.
However, the Java ecosystem supports certain elements that make extensive scaling a complicated affair. These include-
Multi-threading Vertical scaling Shared memory states Monolithic components Multi-layer structure.
You can think out-of-the-box or hire Java developers with the right experience and skill to implement sustainable scalability in a Java system. So, it’s not an entirely lost game. However, scaling with Java requires the understanding of multiple components, their purposes, and their utility.
Python code is hard to maintain when scaling the system. It is a dynamically-typed scripting language, and hence, it typically performs slower than a programming language would. A Python code is plain text that’s interpreted at run-time. As the code grows, so does the amount of text. Eventually, the system becomes too tangled, and tracking points can be lost.
4. Java Vs. Node.js Vs. Python: Simplicity
The simplicity of a programming language is affected by its syntax, expressions, and concepts. The easier a language is to write, the smoother its learning curve becomes. When choosing between Node.js Vs. Python Vs. Java, simplicity matters a lot to a developer that isn’t entirely fluent in the target language.
Java:
The syntax of Java is very similar to C/C++, with the only difference being that it was built exclusively on the principles of object-oriented programming. It is simpler, lighter, compact, and very easy to catch on for anyone with a decent inkling of basic OOP concepts.
And yet, Java programming is neither the easiest nor the most complicated language to learn. You don’t need to understand the intricacies of memory management or garbage collection. The syntax can be grasped quickly. But, while it is easy to learn, it can be harder to learn well.
Python:
On the other hand, Python is a very easily readable programming language. It sports visually simplified formatting, English language keywords, and minimal syntactic exceptions. As a result, it has a streamlined learning curve. The syntax of Python helps developers avoid additional code while facilitating better expression and organization. Overall, it helps in easy code maintenance and up-gradation. It is easier to understand and versatile in implementation.
Node.js:
As far as syntax goes, Node.js is easy. The learning curve for Node.js is short, owing to the relative simplicity of JavaScript, but also steep in places.
Understanding its run-time environment can prove challenging. Implementing asynchronous programming requires a close inspection and mastery of async hooks, patterns, behavior, and syntax. Aso, the run-time environment is distributed in several concepts that you must go through to create a Node.js backend successfully.
5. Java Vs. Node.js Vs. Python: Community
All three languages have established themselves in their niche markets. Both Java and Python are more than two decades old. So naturally, they enjoy diverse, globally distributed communities with active members and a lot of contributions. Node.js is a relatively newer technology. Despite that, it has a sizable community.
6. Java Vs. Node.js Vs. Python: Library
The Python programming language offers a volley of libraries- a standard collection of functionally advanced modules with great potential. Every Standard Library update comes with complete documentation on how to utilize this backend technology stack best. This extensive library offers a wide range of facilities and provides many standardization solutions, thus making coding convenient.
As a 26-years-old language, Java has a voluminous collection of open-source libraries. They cover almost all major programming concepts in Java. You can also find multiple resources for a single task.
When working with Node.js, you will find NPM (Node.js Package Manager.) It is a free online repository that fuels and simplifies JavaScript development by storing Node.js packages. With more than 11 million developers tuned into the NPM and over one million packages to choose from, this software registry easily takes the cake between Node.js Vs. Java Vs. Python.
7. Java Vs. Node.js Vs. Python: Performance by Cost
The total cost of development and launch for Java, Node.js, or Python depends on several factors. But, the overall figure remains cost-effective in most cases.
Python:
Python helps minimize software development costs in different ways. It offers a wide range of open-source assistance in the form of frameworks, tools, and libraries. Its syntax ensures fast development and easy code maintenance. With its numerous libraries, you can create large, multi-tier solutions without devoting extra time or effort. And, with a heavily test-driven approach, Python makes it easier for you to meet project requirements with quality outcomes in time.
Node.js:
How much would it cost to develop Node.js applications or contract a NodeJS development company?
Nothing for the framework or NPM since they are open-source. Additional third-party integrations, APIs, payment gateways, third-party services, or additional support would be the only costs. You may also incur an expense if you choose to hire NodeJS developers.
Java:
Java has always been free. That changed in April of 2019 when Oracle JDK 8 imposed restrictions on commercial use. Oracle announced several changes to its JDK distribution and support systems. You can continue to use Oracle JDK 8 without any further updates. Or, you can get full paid support for JDK 8, OpenJDK8, and OpenJDK 11 binaries.
8. Java Vs. Node.js Vs. Python: Cross-Functionality
JAVA is the mascot of ‘Code Once, Run Everywhere.’ That agility makes it an ideal choice for developing mobile, web, database, and network solutions for a wide variety of functional objectives.
The interpreted nature of Python can be utilized to run a single code on multiple machines. There is no need for recompilation or code alteration. Since Python also supports a wide range of platforms, operating systems, and tools, it is a wonderful, time-saving tool for cross-functional web solution development.
Node.js works wonderfully on multiple devices, platforms, and systems. It can be used to create websites, web, app, or desktop applications, and cloud-based IoT solutions with ease.
Use Cases for Java, Node.js, and Python
Most Popular Use Cases of Node.JS:
Backend and servers
Streaming Real-time updates
Shared document editing
Conferencing
Chat applications
Single-page applications
Microservices
IoT-based applications
APIs Scripting
Most Popular Use Cases of Java:
Website development
Automation apps
Games
Big Data
Cloud Mobile applications
Most Popular Use Cases of Python:
Web development
Data engineering
Machine learning
Artificial intelligence
GUI
Enterprise applications
Games
Conclusion: The Best Backend Technology Stack Is One That Complements Your Project
So far, you have seen the most critical constraints that can help you better analyze the NodeJs Vs. Python Vs. Java situation. And, you have their best use cases in hand.
With me so far?
Great!
Now, I want you to take a deep look at your project and answer these questions.
- What are you building?
Website
Enterprise app
Security solution
Computing solution
Analytic solution
2. Which programming language are you or your team comfortable with?
3. Are you looking to hire software developers for the skill gaps?
If your team is not sufficient, would you hire Python developers or Java or NodeJS resources? Would your budget and work culture allow such outsourcing?
4. What is an acceptable user experience for your app?
What is your target user profile?
5. What are your proposed solution’s environmental constraints?
6. How much load do you expect to put on your app?
7. What are your expected immediate and long-term scaling requirements?
Use these questions to get a better idea of the limitations of your project. Match them with the constraints we discussed here. Then, ask yourself one last thing.
8. Is it cost-effective for you?
This exercise will help you act on the information given here and drive you towards your project's best backend technology stack. If you still harbor questions about NodeJs Vs. Java Vs. Python, let me know in the comments.
