WebSockets vs. Server-Sent Events: Real-Time Communication

As businesses demand instant updates, choosing between WebSockets and Server-Sent Events is crucial for real-time communication strategies. This article from Arvucore compares websockets vs. sse, examines push notifications and streaming patterns, and helps technical and business leaders decide based on performance, scalability, browser support, and developer complexity in modern web and mobile systems.

Core concepts and protocol differences

WebSockets open a bidirectional, full-duplex channel by upgrading an initial HTTP(S) request with an Upgrade: websocket handshake and switching protocols. The browser exposes a WebSocket object that can send binary or text frames, and the protocol defines opcodes, fragmentation, and ping/pong keepalives. Server‑Sent Events (SSE) reuse a plain HTTP(S) GET that the server answers with Content-Type: text/event-stream and then never closes; the browser’s EventSource API exposes a simple event stream, automatic reconnect with Last-Event-ID support, and text-only messages framed by lines prefixed with "data:".

The handshake contrast matters. WebSocket requires an explicit HTTP Upgrade that some proxies or corporate middleboxes block if they don’t speak the protocol. SSE looks like ordinary streaming HTTP and therefore passes many intermediaries more easily, but that same HTTP path makes some proxies buffer or close idle streams unexpectedly. Message framing yields different developer models: WebSockets give you fine control, lower framing overhead for binary payloads, and explicit close semantics; SSE is simpler — human-readable events with built-in reconnection and lower client code complexity.

Practically: choose WebSockets when you need true bidirectional traffic, binary efficiency, or sub‑50ms interaction for interactive apps (chat, collaborative editing). Choose SSE for server-to-client push where browser simplicity, automatic reconnect, and easier proxy traversal matter (live feeds, notifications). Expect connection overhead at setup for WebSockets (Upgrade, stateful sockets) and slightly higher per-message latency jitter for SSE when HTTP chunking and proxies interfere. Common failure modes include intermediary timeouts, TLS termination disrupting upgrade, and mobile networks killing idle sockets; mitigate with heartbeats, exponential reconnect, and server timeouts tuned to real client patterns.

Performance, scalability, and network considerations

Performance and scalability hinge on different bottlenecks for WebSockets and SSE. WebSockets optimize low-latency, high-throughput two‑way streams: binary frames, smaller framing overhead, and fewer protocol round‑trips make them better for chat, gaming, and frequent bi‑directional updates. That comes at the cost of heavier per‑connection state: file descriptors, event-loop memory, and subscription metadata. SSE is lighter per connection (simple text streams over HTTP), easier to route with standard HTTP stacks, and often cheaper when updates are infrequent and unidirectional.

Throughput and latency depend on message size and rate. A simple planning formula helps: total bandwidth ≈ clients × messages/sec × average message size. For example, 50k clients at 1 msg/sec of 1 KB requires ~50 MB/s sustained. Latency tails matter: measure p50/p95/p99 under realistic churn. WebSockets typically yield lower p95 for small messages; SSE can show higher latency under HTTP/1.1 head‑of‑line constraints but benefits from HTTP/2 multiplexing when available.

Concurrent connections are limited by OS fd limits, proxy behavior, and server model. Use event‑driven servers (Nginx, Envoy, Node with clustering, or Go) to minimize per‑connection cost. Beware proxies and CDNs: many CDNs either block or terminate long WebSocket connections or enforce idle timeouts; some support WebSockets only on specific plans. SSE works transparently with HTTP LBs but can still be killed by aggressive timeouts.

For scaling, prefer stateless frontends with a shared pub/sub (Redis, NATS, Kafka) for fan‑out, and autoscale by connection counts. WebSockets often require sticky sessions or a gateway that routes to the right backend; SSE can use simple HTTP load balancing. Cost trade‑offs: WebSocket fleets typically need more instances and specialized gateway capacity; SSE can reduce instance count but increases bandwidth and re‑connect churn. Empirically validate with incremental load tests, track connection churn and memory per connection, and tune OS limits, keepalive intervals, and LB timeouts before selecting the production architecture.

Use cases, patterns, and push notifications

Map each product need to the simplest reliable tool that meets functional constraints, then add bridges for the rest. For interactive two‑way apps (collaborative editors, multiplayer UI, chat), WebSockets are the default: low round‑trip latency, bidirectional conversational semantics, and immediate server pushes fit UX expectations. For read‑heavy live dashboards (metrics, logs, monitoring panels), Server‑Sent Events (SSE) is often sufficient — simple HTTP connections, automatic reconnection semantics, and lower client complexity make it attractive for one‑way streaming where browser background activity isn’t critical.

Financial market feeds and trading desks demand sub‑100ms updates, ordered delivery, and often authenticated channels. WebSockets or dedicated low‑latency feeds win here; consider fan‑out layers (Redis/Kafka) to scale and multicast/caching for repeated snapshots. IoT telemetry is mixed: constrained devices commonly use MQTT (often over WebSockets for browser access); backends should route device telemetry into a message bus and expose dashboards via SSE or WebSockets depending on interactivity.

Push notifications require platform push services (APNs, FCM, Web Push) when devices are backgrounded or offline. Practical pattern: streaming channel for live UX + notification bridge for out‑of‑band alerts. Implementation blueprint: an event bus (Kafka/Redis) -> adapter workers that deliver to connected sockets/SSE streams; if no active session, enqueue to push service with rate limiting, deduplication, and user preference checks.

Hybrid examples: trading app with WebSocket order flow + SSE market overview + FCM price alerts; IoT ops with MQTT ingress, Kafka core, SSE dashboards, and Web Push for critical alarms. Choose by interaction model, battery/background constraints, and delivery guarantees rather than raw protocol zeal.

Implementation best practices, security, and operational readiness

Treat transport security and authentication as first-class requirements. Enforce TLS (1.2+) with automated certificate rotation, HSTS where applicable, and use short-lived credentials for socket connections — JWTs with refresh via a secure channel, OAuth2 tokens, or mTLS for high-assurance links. For WebSockets validate the Origin header and implement strict CORS for SSE; never rely on obscurity. Bind tokens to session metadata (IP, client id) to reduce token replay risk.

Design reconnection and continuity pragmatically. Use exponential backoff with jitter and caps, provide resume semantics (last-event-id for SSE, sequence numbers or resumable session IDs for WebSockets), and surface clear client-side retry policies. Handle backpressure by enforcing per-connection queues, dropping or batching low-value messages, and surfacing signals when a client is slow. Consider application-level ACKs or idempotency keys to preserve ordering and to allow safe retries.

Operational readiness demands observability and measurable SLAs. Emit connection counts, open/close rates, message throughput, latencies, auth failures, reconnection storms, and backpressure events to metrics. Correlate structured logs and traces with connection IDs and user IDs for incident triage. Implement health probes, heartbeat/ping-pong, and automated alerts for anomalous reconnection rates.

Plan graceful fallbacks and rollouts. Provide long-polling or SSE fallback for limited clients, and integrate platform push for mobile/low-power scenarios. Run POCs and staged traffic, run load and chaos tests, and codify retention, encryption, and privacy requirements to meet compliance. Arvucore recommends clear SLAs, observable POCs, and incremental rollouts with feature flags as the path to production confidence.

Conclusion

Choosing between websockets vs. sse depends on bidirectional needs, scale, and latency. WebSockets suit two-way interactive apps while SSE is simpler for unidirectional updates and lightweight push notifications. Evaluate infrastructure cost, browser and mobile support, security, and fallbacks. Arvucore recommends proof-of-concept testing with real workloads, observability, and clear SLA targets before committing to a production architecture.