Real-Time Data Streaming with Spring WebFlux and SSE

I recently built a real-time data streaming solution using Spring WebFlux and Server-Sent Events (SSE) to push short bursts of data to customers via an API. Here’s why it worked and how it stacks up. I needed a lightweight, secure way to deliver short-duration updates. SSE won over alternatives: Vs. Kafka/Pulsar: Too heavy for my needs—SSE is simpler, no broker required. Vs. Long Polling: Less efficient—SSE uses one connection, not constant requests. Vs. WebSockets: Overkill for one-way data—SSE is simpler and secure by design. SSE shines because it’s: Lightweight: Runs on HTTP, low overhead. Great for Short Bursts: Perfect for event-driven updates. Simple: Easy to set up and use. Secure: One-way flow plus custom logic (e.g., auth, filtering). Scalable: Handles concurrency well. Spring WebFlux Boost Spring WebFlux made it real-time and scalable: Reactive: Non-blocking, ideal for streaming. Scalable: Manages tons of connections effortlessly. Flexible: Easy to add auth and filtering. The Result Customers hit an API, get authenticated, and receive filtered, real-time data over SSE. It’s fast, secure, and scales with WebFlux’s reactive power. When to Use It SSE is best for one-way, short-burst updates. Need two-way? Try WebSockets. Big data pipelines? Kafka or Pulsar. For my case, SSE nailed it. Takeaway Spring WebFlux + SSE = a clean, efficient streaming solution. Try it if you need simple, real-time data delivery. Thoughts? Share below!

Feb 22, 2025 - 14:30

Real-Time Data Streaming with Spring WebFlux and SSE

I recently built a real-time data streaming solution using Spring WebFlux and Server-Sent Events (SSE) to push short bursts of data to customers via an API. Here’s why it worked and how it stacks up.

I needed a lightweight, secure way to deliver short-duration updates. SSE won over alternatives:

Vs. Kafka/Pulsar: Too heavy for my needs—SSE is simpler, no broker required.
Vs. Long Polling: Less efficient—SSE uses one connection, not constant requests.
Vs. WebSockets: Overkill for one-way data—SSE is simpler and secure by design.

SSE shines because it’s:

Lightweight: Runs on HTTP, low overhead.
Great for Short Bursts: Perfect for event-driven updates.
Simple: Easy to set up and use.
Secure: One-way flow plus custom logic (e.g., auth, filtering).
Scalable: Handles concurrency well.

Spring WebFlux Boost

Spring WebFlux made it real-time and scalable:

Reactive: Non-blocking, ideal for streaming.
Scalable: Manages tons of connections effortlessly.
Flexible: Easy to add auth and filtering.

The Result

Customers hit an API, get authenticated, and receive filtered, real-time data over SSE. It’s fast, secure, and scales with WebFlux’s reactive power.

When to Use It

SSE is best for one-way, short-burst updates. Need two-way? Try WebSockets. Big data pipelines? Kafka or Pulsar. For my case, SSE nailed it.

Takeaway

Spring WebFlux + SSE = a clean, efficient streaming solution. Try it if you need simple, real-time data delivery.

Thoughts? Share below!