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Python vs JavaScript: Backend Battle in 2026

Explore Python and JavaScript backend performance with FastAPI and Bun. Key insights into latency, throughput, and more.

Yuki Okonkwo

Written by AI. Yuki Okonkwo

December 30, 20253 min read
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Python logo with upward trend line on left, cheerful character on right with performance graphs comparing both languages

Photo: Anton Putra / YouTube

In the tech arena of backend development, two heavyweights are duking it out for supremacy: Python and JavaScript. Each language brings its own set of strengths and quirks to the table, but when it comes to performance, which one takes the crown?

Anton Putra's recent video dives into this very question, using FastAPI for Python and Bun for JavaScript to compare metrics like latency, throughput, CPU, and memory usage. If you're all about the numbers, buckle up—this exploration is as detailed as it gets.

FastAPI: Python's Speed Racer

Python, the darling of data science and AI, shines brightly with its simplicity and readability. FastAPI, a web framework for building APIs with Python, is no slouch either. In the tests, FastAPI managed to handle around 28,000 requests per second, a testament to its efficiency under high loads.

"Python was created in the late 1980s and got its first release in February 1991," notes Putra, highlighting its longstanding presence in the programming world.

Python's popularity isn't just about its speed; it's about community, too. The language evolved through community-driven enhancements, and its ecosystem is rich with libraries like Pandas, NumPy, and Scikit-learn. FastAPI itself benefits from ongoing community contributions, with multiple pull requests aimed at boosting its performance further.

Bun: JavaScript's New Contender

JavaScript, the backbone of web development, has extended its reach into the backend with the introduction of Bun. Developed to enhance performance over Node.js, Bun is making strides as a JavaScript runtime. However, it's not without its hiccups.

In the tests, Bun's connection management revealed some challenges. "When you configure a database connection in your application, you have an option to set a maximum lifetime for inactive connections," explains Putra. Bun's approach to scaling connections isn't gradual. Instead, it maxes out the allowed connections, leading to potential inefficiencies.

Despite these hurdles, Bun's ability to process a high number of requests per second shows promise, especially with fine-tuned configurations. It's a reminder that while JavaScript's ubiquity in browsers has made it a convenient choice for full-stack development, backend optimization requires careful attention to detail.

The Bigger Picture: Community and Configuration

Both FastAPI and Bun underscore the importance of understanding underlying architecture and configuration options for optimizing backend performance. Whether it's managing connection pools or tweaking runtime flags, the devil is in the details.

Moreover, the open-source nature of these technologies invites collaboration and innovation. Putra himself received multiple pull requests to improve both applications, reflecting a community-driven approach to enhancing performance.

The Verdict?

So, which language reigns supreme in the backend battle? It depends. Python's FastAPI shows robustness and a supportive community, making it a solid choice for AI and data science-heavy applications. JavaScript's Bun, while still finding its footing, offers the allure of using a single language across the stack and has the potential to improve with ongoing development.

Ultimately, the choice between Python and JavaScript hinges on your specific use case, existing tech stack, and willingness to dive into the intricacies of backend optimization.

Curious to dig deeper? Check out Anton Putra's video for a full rundown of the tests and their results.

By Yuki Okonkwo

TagsPython
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