🔄 Server-Sent Events (SSE) vs WebSockets vs Long Polling: What’s Best in 2025?

Real-time data is everywhere in 2025 — whether you're building stock dashboards, multiplayer games, or live chat apps. But should you use WebSockets, SSE, or Long Polling?

This post breaks them down with real-world examples, pros & cons, and beginner-friendly code snippets.

📦 TL;DR

🎯 Use Case: Live Order Status in an eCommerce App

Imagine you're building a real-time order tracking feature.

A user places an order and wants to see status updates as it progresses: "Confirmed → Packed → Shipped → Delivered"

Let’s implement this with all three options.

🧵 1. Long Polling (Legacy but still used)

How it works:

Client sends a request → Server holds it open until data is available → Responds → Client starts again.

// Client-side (JS)
setInterval(() => {
  fetch("/order-status")
    .then(res => res.text())
    .then(console.log);
}, 3000); // Poll every 3 seconds

Spring Boot Controller (pseudo):

@GetMapping("/order-status")
public ResponseEntity<String> getStatus() {
    String status = orderService.getLatestStatus();
    return ResponseEntity.ok(status);
}

✅ Pros:

• Simple to implement
• Works with old infrastructure ❌ Cons:
• Wastes bandwidth (even when nothing changes)
• Higher latency and server load

🔄 2. Server-Sent Events (SSE)

How it works:

A single HTTP connection where the server pushes updates as they happen.

Spring Boot Server:

@GetMapping(value = "/order-stream", produces = MediaType.TEXT_EVENT_STREAM_VALUE)
public Flux<String> streamOrderStatus() {
    return Flux.interval(Duration.ofSeconds(2))
               .map(i -> orderService.getLiveStatus());
}

Client (JS):

const source = new EventSource("/order-stream");

source.onmessage = function(event) {
  console.log("Order Update:", event.data);
};

✅ Pros:

• Easy setup with HTTP
• Built-in reconnect
• Lightweight for 1-way data ❌ Cons:
• Only server ➡️ client
• Not supported in older browsers or HTTP/2+

🔄🔁 3. WebSockets (For Real-time, Bi-directional Apps)

How it works:

Client and server establish a persistent connection for 2-way data flow.

Spring Boot WebSocket Config:

@Configuration
@EnableWebSocket
public class WebSocketConfig implements WebSocketConfigurer {
    public void registerWebSocketHandlers(WebSocketHandlerRegistry registry) {
        registry.addHandler(new OrderWebSocketHandler(), "/ws/orders");
    }
}

Java WebSocket Handler:

public class OrderWebSocketHandler extends TextWebSocketHandler {
    @Override
    public void handleTextMessage(WebSocketSession session, TextMessage message) {
        // Send real-time status
        session.sendMessage(new TextMessage("Shipped"));
    }
}

Client:

const socket = new WebSocket("ws://localhost:8080/ws/orders");

socket.onmessage = (e) => {
  console.log("Update:", e.data);
};

✅ Pros:

• Real-time, bidirectional
• Efficient for interactive apps ❌ Cons:
• Harder to scale
• Needs WebSocket support in infra (load balancer, proxy, etc.)

🧠 Which One Should I Use?

🧪 Bonus: Performance Tips

• For high-frequency updates, use WebSockets with message batching.
• Use SSE for server-to-client streams like:
  • Logs
  • Stock prices
  • Notifications
• For mobile networks or flaky connections, SSE reconnects automatically.
• Avoid Long Polling unless compatibility is a must.

✅ Final Thoughts

Each technique has a purpose. Don’t just default to WebSockets — sometimes SSE is better for one-way updates, and Long Polling works in legacy APIs.

Start simple, and only level up when your use case demands it.

💬 What’s your go-to for real-time features in Java? Drop your comments or share your favorite stack!

👋 Follow me for more Java, Spring Boot, and backend real-time architecture deep dives!

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Would you like me to:
- Add some visuals or diagrams for connection flows?
- Turn this into a live working GitHub repo?
- Add a part 2: scaling SSE or WebSockets with Redis / Kafka?

Let’s build it together if you’re planning to post it soon!