Best practice to implement a low latency live financial data feed using WCF?

I have a .NET service which need to feed live financial data to its clients. The output rate for this feed might get intense and I am looking for the best architecture to implement this type of service with low latency and high performance.

I was thinking of using some kind of a stream data provider, one that is used for audio or video, but send feed updates instead.

Would appreciate any thought on this subject, or any real world examples


I don't have to use WCF, that was only my first approach since it is the current technology. Any other implementation in C# is welcome.


Full Disclosure: I work for Informatica (formerly 29West) and am on the engineering team responsible for their messaging products. I am biased. I do, however, have a pretty good grasp of low-latency messaging in the financial market.

If you message rates are about 60 messages/sec. (as stated in a comment on Will Dean's answer), and they're being delivered to a GUI with a human sitting in front of it and reacting to the market at human-speed, it honestly doesn't matter a whole lot what software you use from a latency perspective. You might even be able to get away with using WCF (though I'd still recommend against it; we considered supporting it once and prototyped an adapter for it and it bloated latencies up by an order of magnitude - we decided not to bother with it at the time).

Now, Informatica's messaging software can pass messages between processes on the same machine in well under a microsecond, and if you want to buy some nice 10 gig-E NICs with kernel bypass or InfiniBand gear, you can pass millions of messages per second between machines with single-digit microseconds of latency. We'll also soon be releasing a new data serialization library that's supported in C/C++, Java, and .NET as part of the messaging product that in some cases is actually faster than Protocol Buffers (although Protocol Buffers are widely used and also a very good choice). Our .NET and Java APIs both have a feature called "ZOD" for "Zero Object Delivery", which is a kinda funny way of saying they generate no new objects during message delivery, meaning no garbage collection pauses & associated latency spikes/outliers. We've got another product called UMDS that's specifically designed to fan out high-speed backbone traffic to slower desktop apps without slowing down the backbone or other clients.

I could go on and on about how great Informatica's messaging software is and I do think it's worth checking out, but this already looks like a straight-up ad, and I'm an engineer, not a sales person. So here's a few pieces of more general advice:

  • If you have a lot of clients receiving the same data, you'll want some flavor of UDP multicast. You'll often want a reliable multicast transport of some kind - the well-known (and free) reliable multicast protocol is PGM. Windows includes an implementation of PGM that's usable in C#; I'll refer you to Mike Rettig's excellent blog post on how to use it if you want to try it out. (I happen to know Mike - he's a smart guy.) Protocol choice is an area in which you get what you pay for; Informatica's messaging includes a reliable multicast protocol loosely based off of PGM (our architect who designed it co-wrote the PGM RFC a long while back), but with a lot of major improvements. Plain PGM might be fine for what you need, though.

  • You want to go with a brokerless/serverless architecture. Have the apps communicate peer-to-peer with nothing in the middle. Avoid extra hops in the message path (which usually means avoid most JMS implementations, avoid almost anything with "queue" in the name somewhere, etc.).

  • Be mindful of how your system behaves when one individual client misbehaves. Can one slow consumer slow down everyone else?

  • There are a lot of OS tuning and BIOS tuning options that can benefit any sort of low-latency messaging, homegrown or bought - things like interrupt coalescing, tying NIC interrupts to a particular CPU core, receive-side scaling (which has historically been terrible when used with UDP on Windows, but should be getting much better in the future), disabling certain CPU power states, etc.

  • Resist the temptation to use built-in object serialization in .NET to send whole objects over the wire - it is orders of magnitude slower than using a simple binary format (like Protocol Buffers, or Informatica's serialization library, or your own binary format, etc.).

If you have more specific questions or need more detail on any of my advice, just let me know!

How low is 'low latency' and how busy is 'intense'? You need to have some idea of what you're aiming for to choose the right approach.

I could supply you some hardware which would respond to 100% of all requests within, say, 20us upto the full capacity of your network hardware, but it would not use WCF much at all.

To a very broad approximation, I would say that things like WCF are very high-level and trade-off ease-of-use and abstraction-for-the-benefit-of-the-programmer against performance (latency/throughput). Whether they trade it off too much for your application needs real numbers.

The lowest-latency, lowest-overhead IP-based protocol in widespread use is UDP - that's why it's used for things like DNS and NTP. It's very scalable at the server, because the server doesn't need to keep any state, and it's very simple to implement on almost any platform. But you do need to be thinking in terms of network packets rather than .NET objects. Do you get to supply the client-end software too?

Live financial data? Never rely on WCF on that. Instead, go with what other industries use. i.e. NASDAQ uses Real-Time Innovations - Data Distribution Service to deliver live stock ticks to users. They provide C/C++/C# api for their communications libraries, which is extremely easy to setup and use (compared to WCF).

In general, this sort of real-time data feeds use publish/subscribe paradigm which helps to make sure that the communication happens with minimal overhead. This sort of an approach is the main idea in message-oriented middle ware and it is exactly what financial services use for real-time stuff.

On a side node, you can deliver real-time audio-video packets using RTI-DDS library, as far as I know, unmanned aerial vehicles like MQ-9 uses again this library to deliver live video & geo-location information to the ground control stations.

There are also free data distribution service libraries but I've no experience in them. You just need to google for it.

Edit: I'm currently prototyping some HMI (human machine interface) software which uses aforementioned RTI-DDS libraries along with two other libraries which have such message oriented architectures, which did work a thread up to now for all my real-time communication needs. Here is a demo: (It will be used in remotely controlling the equipment in our brand new nuclear research facility)

The more assumptions you make and features you cut out the faster you can make your system. The more robust and flexible you attempt to make things, the more your performance will suffer. I would suggest a few basic must haves:

  1. A binary data serialization format. Don't use XML or any other human readable method of passing your data.
  2. A robust enough data serialization format that it can support cross-architecture, cross-language endpoints. BER comes to mind - C# seems to have support
  3. A transport protocol that has guaranteed delivery and data integrity. If any type of financial algorithm will be using this data, even missing one tick could mean the difference between and order being triggered or missing out on a price. Even if you are going to aggregate ticks in your server you still want control over how the information is presented to your clients. TCP works for distributed systems. However there are much faster alternatives if your clients are on the same machine as your server. UDP won't even garauntee order, which can be problematic (though not insurmountable).

With regard to internal processing:

  1. Avoid strings and other classes that add significant overhead to simple tasks. Use basic character arrays instead. I'm not sure what options you have in C# or if you even have lightweight alternatives. If so, use them. This applies to data-structures as well.
  2. Be aware of double/float comparison errors. Use comparisons that only check for the necessary level of precision. If possible convert everything to integers internally and provide enough metadata to convert back on the other end.
  3. Use something similar to pooled allocators in C++. My lack of knowledge of C# prevents me from being more specific. Again C# probably isn't your best choice here. Bottom line is that you are going to be creating and destroying a lot of tick objects and there is no reason to ask the OS for the memory every time.
  4. Only send out deltas, don't send information that your clients already have. This assumes you are using a transport with guaranteed delivery. If not you could end up displaying stale data for a long time.

This might be of interest although its specific to gaming ... Lowest Latency small size data Internet transfer protocol? c#

Here is a tutorial on UDP connection

Another Article on UDP

You ask specifically about a "low latency User Feed". What do you really want with low latency, for 'Feed Only' (and especially if it does not generate revenue), could the Users wait a second; that is not low latency.

If you want to trade FAST then you need to physically move across the street from the Exchange (or nearby with an Optical Link). Next you need to 'Trade on the Card'; the Ethernet Card is 'smart' and is fed 'Trade Formulas' that program the Network Card to make a preprogrammed trade based on Data received (without pestering your Computer).


Learning to manipulate that Environment will buy you more than reinventing the wheel.

Ultra low latency is costly, but billions are at stake; your stakes (and pursuit of lower latency) with be throttled by $.

In the past i've used Tibco rv or raw sockets for streaming prices/ rates, where high frequency updates are expected. In this situation, it is often the client (or in in fact the user) who is the limitation (as there is only so many updates a user can process), and this is therefore an example of where you can 'lose' data. In this situation a client side service broker can be used to throttle updates.

If the system is used for automated trading or HFT then products like 29West LatencyBuster has been proven to work well and offers guaranteed messaging.

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