Spring MVC vs WebFlux: A Practical Look at Concurrency and Performance

In the Java backend world, Spring MVC has long been the go-to framework. It’s simple, reliable, and works well for most business apps. But as we move into AI inference, video processing, and high-concurrency workloads, a traditional blocking model starts to struggle. That’s where Spring WebFlux comes in. Spring WebFlux a reactive, non-blocking programming model designed to handle thousands of requests without running out of threads.

In this post, I’ll walk through the key differences between MVC and WebFlux, share some benchmark results, and highlight when you should (or shouldn’t) choose WebFlux.

1. Thread Model: How They Handle Requests

Spring MVC (Blocking)

• Built on Servlet + Tomcat
• One request = one thread
• If a task (e.g., AI inference) takes 300ms, that thread is blocked the whole time
• With enough concurrent users, the thread pool fills up and requests start waiting

Think of one waiter who takes your order and then personally goes to cook and bring your food. Works fine for a few tables, but falls apart in a busy restaurant.

Spring WebFlux (Non-Blocking)

• Built on Netty + Reactor
• Threads handle incoming requests and immediately release them to the reactive pipeline
• When the result is ready, Reactor finds the correct connection and writes the response

The waiter only takes orders, while the kitchen and another runner handle food delivery. The waiter is free to serve new customers right away.

2. FAQs You Might Wonder About

Q1: Where is the connection stored if threads get released?
Netty manages it. Each request has a channel bound to an event loop. Even if threads change, the channel stays alive.

Q2: Who writes the response back? When the async task (Mono/Flux) completes, Reactor picks up the right channel and pushes the result.

3. Code Comparison

MVC Controller

@PostMapping("/check")
public ModerationResult check(@RequestPart("file") MultipartFile file) throws Exception {
    return service.classify(file);
}

WebFlux Controller

@PostMapping("/check")
public Mono<ModerationResult> check(@RequestPart("file") MultipartFile file) {
    return fluxService.classify(file);
}

Looks almost the same — but under the hood, the runtime behaves very differently.

4. Benchmark: MVC vs WebFlux

We stress-tested both APIs locally with 200 concurrent users using JMeter.

(Remember: this was CPU-only, no GPU acceleration — so the absolute numbers look slow. What matters here is the relative difference.)

Key Takeaways

• Stability: Both had zero errors
• Latency:
  • MVC = consistently high (32–47s)
  • WebFlux = much lower on average (~27s) but with a long tail (some requests hit ~141s)
• Throughput: MVC slightly higher (because threads were blocking), but not sustainable at scale
• Scalability: WebFlux shines — it avoids thread pool exhaustion, which is critical in real production workloads

5. When to Use WebFlux

Great for:

• AI model inference (image, text, video)
• Long-running, high-concurrency APIs
• API gateway layer (routing, rate-limiting, monitoring)

Less ideal for:

• Simple CRUD apps (MVC is easier)
• Teams new to reactive programming (steep learning curve)

6. Conclusion

Spring MVC and WebFlux are not rivals. In contrast, they are complementary.

• MVC is perfect for 80% of standard business APIs
• WebFlux is better for high-concurrency, resource-intensive workloads

In our benchmark, WebFlux showed lower average latency and stronger concurrency handling, even though it suffered from long-tail requests. In real production, with GPU acceleration, batching, or distributed inference, WebFlux’s advantage grows even bigger.

The future is hybrid: use MVC where it makes sense, and WebFlux where performance and scalability matter most.

Related Resources

• Spring WebFlux Documentation
• Project Reactor Reference Guide
• Related post: Building an AI Moderation API with Spring Boot & WebFlux
• Related post: JNI Preprocessing for ResNet in Java DJL