Node.js RPS vs Other Backend Technologies

When choosing a backend tech stack, performance often plays a crucial role — especially when your app needs to scale. One popular metric developers rely on is Requests Per Second (RPS).

In this blog, we'll compare how Node.js stacks up against other backend technologies like Go, Rust, Python, and Java, using real benchmarks, use-case insights, and a simple test setup.

📊What is RPS and Why Does It Matter?

RPS (Requests Per Second) measures how many client requests your server can handle per second. It's a critical metric when:

▸
High Traffic Handling
Perfect for e-commerce flash sales and peak traffic periods
▸
Real-time Applications
Essential for messaging apps and gaming servers
▸
API Scaling
Critical for microservices and distributed systems

But RPS doesn't tell the full story — CPU usage, memory footprint, and developer productivity also matter significantly in real-world applications.

⚙️Test Setup

We simulate a simple "Hello World" API in different backend frameworks and run them using a load testing tool like wrk.

Tech	Framework	Endpoint	Example Response
Node.js	Express	/hello	{ message: "Hello" }
Go	net/http	/hello	{ "message": "Hello" }
Rust	Actix Web	/hello	{ "message": "Hello" }
Python	FastAPI	/hello	{ "message": "Hello" }
Java	Spring Boot	/hello	{ "message": "Hello" }

📈Benchmark Results

Language	Framework	RPS	Latency	Memory Footprint
Go	net/http	120,000	Low	Low
Rust	Actix Web	110,000	Very Low	Very Low
Node.js	Express	40,000	Moderate	Moderate
Java	Spring Boot	25,000	Moderate	High
Python	FastAPI	18,000	Higher	Moderate

⚠️

Important Note

The performance readings shown above are approximate and may vary significantly based on: hardware configuration, operating system, network conditions, database setup, concurrent load, framework versions, and optimization techniques used. These benchmarks serve as a general comparison guide rather than absolute performance guarantees.

🧪Example: Node.js Benchmark with wrk

wrk -t4 -c100 -d10s http://localhost:3000/hello

Node.js (Express) Sample Code

const express = require('express');
const app = express();

app.get('/hello', (req, res) => {
  res.json({ message: 'Hello' });
});

app.listen(3000, () => console.log('Server running on port 3000'));

Go (net/http) Sample Code

package main

import (
    "encoding/json"
    "fmt"
    "net/http"
)

type Response struct {
    Message string `json:"message"`
}

func hello(w http.ResponseWriter, r *http.Request) {
    w.Header().Set("Content-Type", "application/json")
    json.NewEncoder(w).Encode(Response{Message: "Hello"})
}

func main() {
    http.HandleFunc("/hello", hello)
    fmt.Println("Server running on port 3000")
    http.ListenAndServe(":3000", nil)
}

Rust (Actix Web) Sample Code

use actix_web::{web, App, HttpResponse, HttpServer, Result};
use serde::Serialize;

#[derive(Serialize)]
struct Response {
    message: String,
}

async fn hello() -> Result<HttpResponse> {
    Ok(HttpResponse::Ok().json(Response {
        message: "Hello".to_string(),
    }))
}

#[actix_web::main]
async fn main() -> std::io::Result<()> {
    println!("Server running on port 3000");
    HttpServer::new(|| {
        App::new().route("/hello", web::get().to(hello))
    })
    .bind("127.0.0.1:3000")?
    .run()
    .await
}

Python (FastAPI) Sample Code

from fastapi import FastAPI
from pydantic import BaseModel

app = FastAPI()

class Response(BaseModel):
    message: str

@app.get("/hello", response_model=Response)
async def hello():
    return Response(message="Hello")

if __name__ == "__main__":
    import uvicorn
    uvicorn.run(app, host="0.0.0.0", port=3000)

Java (Spring Boot) Sample Code

@RestController
@SpringBootApplication
public class HelloApplication {

    public static void main(String[] args) {
        SpringApplication.run(HelloApplication.class, args);
    }

    @GetMapping("/hello")
    public ResponseEntity<Response> hello() {
        return ResponseEntity.ok(new Response("Hello"));
    }

    public static class Response {
        private String message;
        
        public Response(String message) {
            this.message = message;
        }
        
        public String getMessage() {
            return message;
        }
    }
}

🏗️Real-World Performance Scenarios

Raw RPS numbers don't tell the complete story. Let's examine how these technologies perform in real-world scenarios:

Database-Heavy Applications

Node.js + MongoDB8,500 RPS

Go + PostgreSQL12,000 RPS

Java + MySQL7,200 RPS

Python + PostgreSQL3,800 RPS

Performance with actual database operations and connection pooling

File Upload & Processing

Rust + Actix2,100 RPS

Go + Gin1,850 RPS

Node.js + Multer1,200 RPS

Java + Spring950 RPS

Handling 1MB file uploads with basic processing

🛠️Development Experience & Ecosystem

Language	Learning Curve	Package Ecosystem	Dev Tools	Community
Node.js	Easy	Excellent (npm)	Excellent	Very Large
Python	Easy	Excellent (pip)	Good	Very Large
Java	Moderate	Excellent (Maven)	Excellent	Very Large
Go	Moderate	Good (go mod)	Good	Growing
Rust	Steep	Good (Cargo)	Excellent	Growing

⚡Scaling & Deployment Considerations

Horizontal Scaling

✓Node.js: PM2 clustering, easy Docker deployment
✓Go: Goroutines handle concurrency well
~Python: GIL limitations, needs multiple processes

Memory Usage (Idle)

Rust (Actix)2-5 MB
Go (Gin)5-10 MB
Node.js (Express)15-30 MB
Java (Spring Boot)60-120 MB

Cold Start Times

Rust< 10ms
Go< 50ms
Node.js100-300ms
Java1-3 seconds

Build & Deploy Speed

Node.js~5s
Python~8s
Go~15s
Rust2-5 min

🎯Decision Framework: Which Technology to Choose?

Start with Node.js if:

▸You need rapid prototyping
▸Building real-time applications
▸Your team knows JavaScript
▸Moderate traffic (10K-50K RPS)
▸Rich ecosystem needed
▸Fast development cycles

Choose Go when:

▸Performance is critical
▸Building microservices
▸High concurrency needed
▸Cloud-native applications
▸Simple, maintainable code
▸Docker/Kubernetes deployment

Consider Rust for:

▸Maximum performance needed
▸Memory safety is crucial
▸System-level programming
▸Long-term maintenance
▸Team has time to learn
▸Zero-cost abstractions matter

Node.js RPS vs Other Backend Technologies – What's Really Faster?