SSE vs WebSockets: which should you use?

Server-Sent Events (SSE) and WebSockets both push data from the server to the browser without the page refreshing. They are often presented as rivals, but they solve different problems. Picking the wrong one means either building more than you need or fighting the protocol later. Here is how to choose, based on running streamed AI answers and live data feeds in production.

The short answer

• Use SSE when the server mostly talks and the browser mostly listens: live dashboards, notifications, progress updates, activity feeds and streaming AI responses token by token.
• Use WebSockets when both sides talk constantly and quickly: chat with typing indicators, multiplayer games, collaborative editing, or anything that needs low-latency messages in both directions.
• If you are unsure, start with SSE. It is simpler to build, debug and scale, and most “real-time” features turn out to be one-way.

How they differ

• Direction: SSE is server-to-client only (the browser still sends normal HTTP requests). WebSockets are fully two-way over one connection.
• Protocol: SSE is plain HTTP with a long-lived response, so it works with your existing auth, cookies, proxies and CDN. WebSockets upgrade the connection to a separate protocol that every proxy and load balancer in the path must support.
• Reconnection: the browser’s built-in EventSource reconnects automatically and can resume from the last event ID. With WebSockets you write reconnection and resume logic yourself.
• Data: SSE sends text (usually JSON). WebSockets can also send binary efficiently.
• Connections: over old HTTP/1.1, browsers limit open connections per domain, which can bite SSE when a user has many tabs open. HTTP/2 removes most of that limit.

Why AI chat products stream over SSE

When a language model writes an answer, it is a one-way stream of text from server to browser — exactly what SSE was designed for. The major AI APIs stream their responses as server-sent events, and it is the natural fit for passing those tokens on to your own users. The question goes up as a normal request, and the answer streams back. You only need WebSockets for an AI feature if it also needs constant two-way traffic, such as live voice.

The production gotchas nobody warns you about

• Buffering kills streaming. Web servers, reverse proxies and compression often hold the response until it is complete, so the user sees nothing and then everything at once. Turn off response buffering and compression for stream endpoints (for example X-Accel-Buffering: no behind nginx) and flush output after every event.
• Idle timeouts. Proxies and CDNs close connections that look idle. Send a small comment line every 15–30 seconds as a keep-alive during long pauses.
• Slow upstream calls stall everything. If one stream waits on an external API or tool, give each call its own timeout so a single slow source cannot freeze the whole response.
• Count your connections. Every open stream holds a connection on your server. Plan for how many concurrent users you expect, and use an event-driven runtime such as Node.js for many simultaneous streams.
• Auth on reconnect. EventSource cannot set custom headers, so authenticate with cookies or a short-lived token in the URL, and make sure reconnections are authorised too.

A simple way to decide

Ask one question: does the browser need to send many small messages quickly while the stream is open? If no, use SSE. If yes, use WebSockets. Many products use both — SSE for the live feed, normal HTTP requests for actions — and never need WebSockets at all.

If you are adding streaming AI answers or a live dashboard to an existing app, my AI integration and real-time development work covers exactly this, including the buffering and timeout details above.