Comet Servers for a Single-Dealer Platform (SDP)

There is a lot more to a Single-Dealer Platform than just a Comet Server, but it is still a key component and often one of the components bought in rather than developed in house. At Caplin we have dedicated much of our time to building what we believe is the Comet server that offers the best performance and feature set on top for building a SDP. Hopefully this post will explain why we believe this, and where you might have more work to do with the other products.

A Comet server allows an SDP to deliver prices and manage trading between a backend system and a browser client – although many will support other clients too. These days there are a number of choices for a Comet server, and more of them are realising that financial data is a great use case and targeting effort in that direction.


If you are choosing a Comet server for an SDP there are a number of questions you should be asking that will have a big impact on the amount of integration and other work you will have to do.

  1. What is the structure of the messages or objects?
  2. Does it support bidirectional messaging?
  3. Can it throttle or conflate fast updating data?
  4. What languages are client APIs available in?
  5. What languages are backend integration APIs available in?
  6. How does it perform with high numbers of users and update rates?
  7. How does it perform in terms of message latency?
  8. How does it integrate with permissions systems and Single Sign On (SSO) ?
  9. How much bandwidth does it use?

Cometdaily covers some Comet servers focusing on the low level technical details that relate to Comet specifically with their Comet Maturity Guide. This is important, however it doesn’t really help differentiate between the offerings for an SDP, and doesn’t really answer all of the questions posted above.

I have looked at a number of Comet servers over the last few years and the following information is based on what I have experienced when I tried them out. Where I have been unable to obtain information directly from trying them out I have acquired it from documentation and performance results published by the providers.

Liberator is of course a Caplin product and many, if not all, of the other servers may be perceived as a competitor in some way. I have tried with best endeavours to be impartial in my assessment but invite comments from all the mentioned vendors if they believe there are inaccuracies about their server, or if they feel I have misrepresented them

Caplin Liberator

Mature C based product focused on finance and trading (Integrates with higher level APIs in Caplin Platform)

Messages/Objects:Field/Value based record objects, plus higher level types such as lists of objects
Client APIs:Good – Javascript, Java, .Net, Silverlight, C, Flex
Server APIs:Good – Java, .Net, C/C++
Performance:Excellent (Published)
Latency:Excellent (Published)
Permissions/SSO:Good – API based / SSO integration built in

The published Liberator benchmarks only show tests where batching was configured. This gives more headroom at the expense of latency. I have recently carried out some tests with zero or much lower batching to get the lowest possible latency with excellent results and without impacting the numbers of users/updates too much. These will be published along with a whole new set of benchmarks in a few weeks time.


Mature Java based product and finance aware.

Messages/Objects:Field/Value based
Bidirectional:Yes – in version 3.6
Client APIs:Good – Javascript, Java, .Net, Silverlight, Flex
Server APIs:Average – Java, .Net
Performance:Good (Unpublished)
Latency:Good (Unpublished)
Permissions/SSO:Good – API based / SSO integration possible

Adobe LCDS

Limited to Flex clients. Not really focused on finance. Integrates well in areas outside of Comet.

Messages/Objects:Object serialisation based
Client APIs:Limited – Flex
Server APIs:Limited – Java
Performance:Average – better in Version 3 (Blog)
Latency:Good (Blog)
Permissions/SSO:Simple API based

LCDS messages can be sent in a number of formats. One is XML based which means message sizes up to 10 times the size of the best here. Using AMF it cuts out XML tags, but still contains a lot of data, eg field names. Messages are still up to 5 times larger than the best here.

my-Channels Nirvana

Messaging server with lots of API support. Probably suits people with the enterprise/message queue/JMS mindset.

Messages/Objects:Opaque and Field/Value based
Conflation:No – opaque messages
Client APIs:Excellent – Javascript, Java, Silverlight, Flex, .Net, C++, iPhone, Android, Blackberry/J2ME
Server APIs:Good – Java, .Net, C++, VBA
Performance:“many thousands” (Unpublished)
Latency:“ultra fast low latency” (Unpublished)
Permissions/SSO:Good – API / SSO integration

Kaazing Gateway

Kaazing Gateway is a WebSocket style server. It is intended to be used to bridge a client to an existing socket based server. This means it is missing many of the features of the other servers, but could be attractive to someone wanting a minimal server to build on top of.

Messages/Objects:WebSocket API only
Conflation:No – opaque socket
Client APIs:Good – Javascript, Flex, Silverlight, Java
Server APIs:Socket interface
Performance:“millions of messages per second” (Unpublished)
Latency:“near zero latency” (Unpublished)
Bandwidth:Dependant on application

Migratory Push Server

Relatively new product that scales to very high numbers of users. Background in RMDS, so finance focused.

Messages/Objects:Field/value based
Bidirectional:No evidence of bidirectional API
Client APIs:Average – Javascript
Server APIs:Average – Java, PHP
Performance:Excellent (Published)
Latency:Good (Published)
Bandwidth:Good – but still sends full topic and field names


The free alternative. There are plenty of other free Comet servers, but I chose to include Jetty/Cometd. This is the main server behind the Bayeux protocol

Messages/Objects:JSON message structures
Client APIs:Average – Javascript, Java
Server APIs:No specific server API
Performance:Average (Blog)
Latency:Long Polling only – not so good for fast updating data
Permissions/SSO:Simple API / SSO Integration
Bandwidth:Good – but still sends full topic and field names

Subscription semantics

One area not covered above is the subscription semantics. Most of the Comet servers here implement some kind of publish/subscribe model. This is implemented in a number of ways though. Pure pub/sub, as I think of it, de-couples producers and consumers completely and a when a consumer subscribes they only receive something the next time that item updates. In financial applications this can be quite limiting.

The first aspect of that, the de-coupling, is inefficient. You don’t want producers of data sending everything on to the next hop in the chain if no one is subscribed to it – it is better if the producer is told when to start and stop publishing for a specified topic. In a fixed income application there could be tens of thousands of instruments, but not all of them will be subscribed to at any one time. For pure pub/sub systems this extra layer of subscription handling is often implemented on top of the core functionality at integration time.

The second aspect is also often implemented as an after thought on top of a messaging system. When a subscription is made to a financial instrument, most of the time you want to see the current values (the image) and receive subsequent updates to those values. Systems that don’t implement this for you leave you open to nasty race conditions if you try and add a cache.


Performance and latency are difficult to compare directly. Even if a head to head bake off is setup, there are numerous variables involved in these kinds of tests, and some servers may fare better in particular scenarios but worse in others. For example Migratory have cleared put some effort into supporting very high numbers of users, something that we haven’t had the demand for at Caplin so our tests have only ever gone up to 30,000 users (which is still a high number for many financial use cases). For some scenarios squeezing out every last drop of latency is priority, whereas others need lots of users and high update rates and can accept a slightly higher, but maybe more predictable, latency.

For a lot of applications predictable latency can be more important than the latency itself. When a price is quoted, with a known latency to the recipients of that price, the latency can be taken into account to cover the risk involved. However, if the latency is unpredictable then the highest likely latency will have to be taken into account when a price is quoted. Alternatively it will be necessary to introduce a threshold that blocks trading on more latent prices, which doesn’t lead to a good user experience.


It is possible to build an SDP with any of these products, but there are two high level reasons why some will be better than others. Features and Performance. In most cases the features mean there will be a lot less work in building your SDP, but you could probably still do it given enough time and money. However, performance may be more of a stumbling block. You may be able to solve it by throwing more hardware at it, but often the nature the of problem is not perfectly scalable and you will still hit issues.

There are other aspects of Comet servers that can help with developing SDPs, I have concentrated on some key aspects that are comparable in some way and hopefully provided some useful information.

7 thoughts on “Comet Servers for a Single-Dealer Platform (SDP)”

  1. Matt’s comment on his blog – (link back above) mentions Stream –
    StreamHub has been on my radar, but they haven’t really come up much yet.
    I’d welcome more vendors to publish performance results, as mentioned we’re just running some new ones ourselves at the moment, as are Adobe.
    I’d also be interested if Lab49 want to collaborate on running some tests, it can be time consuming though!

  2. Hi John. Yes, that would be good. Testing Comet servers isn’t trivial due to the large numbers of clients needed, so specialised test harnesses (or tons of machines) are needed which means a fair bit of work to do it for a number of products.
    Maybe some kind of test and hardness spec could be written and vendors submit their own tools do the vendor specific stuff.

  3. Paul’s sweeping attempt at classifying everything that might offer a realtime messaging capability via the Internet as Comet demonstrates a lack of understanding of the issues faced when implementing such multi platform streaming solutions for SDP. Comet, while relevant, in no way represents every product in this space, it simply (as the wiki link he included states) represents a number of techniques that enable the streaming of data from a server to a browser.
    Nirvana ( ) supports Comet ( and the WebSocket protocol )for our Javascript browser based clients however we do so much more than Comet for all of our other supported Enterprise, Web and Mobile clients.
    While the 9 questions Paul defines are relevant they are far from complete and although integration is mentioned in the prequel to the list it is subsequently glossed over. To establish a more complete list of discussion points to aid these types of technology decision one might also include:
    – Support for clustering and failover approaches this enabling compliance with business contingency policies.
    – Support for standards. Things like HTML5 WebSocket support, AMQP, JMS etc.
    – Support for integration with 3rd party technologies. Not just back end but client side integration for end to end B2B type solutions
    – Support for integration with existing enterprise management technologies. Measuring end to end latency is only possible if the underlying technologies used supports such functionality and expose it in administration and management API’s and tools.
    – Security, not just SSO but an understanding of authentication and entitlements and how such functionality can be leveraged in client implementations
    – Configuration management, both client and server. Snapshotting production environments, being able to roll back configurations and quickly deploy new instances.
    – Support for different messaging paradigms. Not everything fits into a publish/subscribe model. Some interactions require point to point or queue based communications.
    – Support for different deployment topologies, i.e broker and brokerless based servers, caching severs and server federation.
    Finally on the subject of performance in our experience clients pay little attention to vendor published results and always understandably insist on establishing what is possible in their respective environments; typically via a vendor bake off. To date Nirvana has proven to be very successful in these real world test case scenarios and consequently is used today by some of the worlds leading SDP implementations.
    Perhaps market share and implementation base should also be included in the questions to be asked !

    1. There is no lack of understanding here – re-read the start, I clearly state that an SDP is more than just a Comet server, but this blog is about Comet servers – since a lot of people DO think that a Comet server is all you need to develop an SDP. This blog is meant to show just a few things that might differentiate Comet servers, even though there is so much more around them when considering a whole SDP stack.
      I don’t think any of your points are wrong, but the blog was not meant to cover everything, it would need a whole series of blogs to do that.
      I think from your list I would pick out failover, latency and authentication/entitlements (although I thought I covered this, reading it back it doesn’t make it clear I was talking about more than just SSO)
      Finally on the subject of performance, in our experience clients pay a lot of attention to our vendor published results and many also want to run their own benchmarks (mainly because scenarios can differ so much) for which we provide a set of tools to do so with.

  4. It’s an interesting comparison but it lacks the most significant factor every buyer needs to address…Pricing! There are HUGE differences between the products mentioned in terms of price models. Any comments?

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