Many Comet implementations like Caplin provide server scalable solutions.
Following is one of the statistics from Caplin site:
A single instance of Caplin liberator can support up to 100,000 clients each receiving 1 message per second with an average latency of less than 7ms.
How does this to compare to HTML5 websockets on any webserver? Can anyone point me to any HTML 5 websockets statistics?
Disclosure - I work for Caplin.
There is a bit of misinformation on this page so I'd like to try and make it clearer..
I think we could split up the methods we are talking about into three camps..
I see them all as Comet, since Comet is just a paradigm, but since WebSocket came along some people want to treat it like it is different or replaces Comet - but it is just another technique - and unless you are happy only supporting the latest browsers then you can't just rely on WebSocket.
As far as performance is concerned, most benchmarks concentrate on server to client messages - numbers of users, numbers of messages per second, and the latency of those messages. For this scenario there is no fundamental difference between HTTP Streaming and WebSocket - both are writing messages down an open socket with little or no header or overhead.
Long polling can give good latency if the frequency of messages is low. However, if you have two messages (server to client) in quick succession then the second one will not arrive at the client until a new request is made after the first message is received.
I think someone touched on HTTP KeepAlive. This can obviously improve Long polling - you still have the overhead of the roundtrip and headers, but not always the socket creation.
Where WebSocket should improve upon HTTP Streaming in scenarios where there are more client to server messages. Relating these scenarios to the real world creates slightly more arbitrary setups, compared to the simple to understand 'send lots of messages to lots of clients' which everyone can understand. For example, in a trading application, creating a scenario where you include users executing trades (ie client to server messages) is easy, but the results a bit less meaningful than the basic server to client scenarios. Traders are not trying to do 100 trades/sec - so you end up with results like '10000 users receiving 100 messages/sec while also sending a client message once every 5 minutes'. The more interesting part for the client to server message is the latency, since the number of messages required is usually insignificant compared to the server to client messages.
Another point someone made above, about 64k clients, You do not need to do anything clever to support more than 64k sockets on a server - other than configuring the number file descriptors etc. If you were trying to do 64k connection from a single client machine, that is totally different as they need a port number for each one - on the server end it is fine though, that is the listen end, and you can go above 64k sockets fine.
In theory, WebSockets can scale much better than HTTP but there are some caveats and some ways to address those caveats too.
The complexity of the handshake header processing of HTTP vs WebSockets is about the same. The HTTP (and initial WebSocket) handshake can easily be over 1K of data (due to cookies, etc). The important difference is that the HTTP handshake happens again every message. Once a WebSocket connection is established, the overhead per message is only 2-14 bytes.
The excellent Jetty benchmark links posted in @David Titarenco's answer (1, 2) show that WebSockets can easily achieve more than an order of magnitude better latency when compared to Comet.
See this answer for more information on scaling of WebSockets vs HTTP.
Caveats:
WebSocket connections are long-lived unlike HTTP connections which are short-lived. This significantly reduces the overhead (no socket creation and management for every request/response), but it does mean that to scale a server above 64k separate simultaneous client hosts you will need to use tricks like multiple IP addresses on the same server.
Due to security concerns with web intermediaries, browser to server WebSocket messages have all payload data XOR masked. This adds some CPU utilization to the server to decode the messages. However, XOR is one of the most efficient operations in most CPU architectures and there is often hardware assist available. Server to browser messages are not masked and since many uses of WebSockets don't require large amounts of data sent from browser to server, this isn't a big issue.
It's hard to know how that compares to anything because we don't know how big the (average) payload size is. Under the hood (as in how the server is implemented), HTTP streaming and websockets are virtually identical - apart from the initial handshake which is more complicated when done with HTTP obviously.
If you wrote your own websocket server in C (ala Caplin), you could probably reach those numbers without too much difficulty. Most websocket implementations are done through existing server packages (like Jetty) so the comparison wouldn't really be fair.
Some benchmarks:
http://webtide.intalio.com/2011/09/cometd-2-4-0-websocket-benchmarks/
http://webtide.intalio.com/2011/08/prelim-cometd-websocket-benchmarks/
However, if you look at C event lib benchmarks, like libev and libevent, the numbers look significantly sexier:
http://libev.schmorp.de/bench.html
Ignoring any form of polling, which as explained elsewhere, can introduce latency when the update rate is high, the three most common techniques for JavaScript streaming are:
WebSocket is by far the cleanest solution, but there are still issues in terms of browser and network infrastructure not supporting it. The sooner it can be relied upon the better.
XHR/XDR & Forever IFrame are both fine for pushing data to clients from the server, but require various hacks to be made to work consistently across all browsers. In my experience these Comet approaches are always slightly slower than WebSockets not least because there is a lot more client side JavaScript code required to make it work - from the server's perspective, however, sending data over the wire happens at the same speed.
Here are some more WebSocket benchmark graphs, this time for our product my-Channels Nirvana.
Skip past the multicast and binary data graphs down to the last graph on the page (JavaScript High Update Rate)
In summary - The results show Nirvana WebSocket delivering 50 events/sec to 2,500k users with 800 microsecond latency. At 5,000 users (total of 250k events/sec streamed) the latency is 2 milliseconds.