Performance

As you can see from the diagram, the factor does not necessarily have to be mutually exclusive e.g. if you want the highest performance and can code in Java/C++ or C then both paths lead you to the Enterprise APIs that form the Refinitiv Real-Time SDKs (RT-SDKs)

Conversely, for a specialised use case like algorithmic trading (which demands the lowest possible latency) the path will lead you to the only choice of the Enterprise Transport API (ETA) which

• Is Open-source, highest performance, lowest latency and is the foundation of the Refinitiv Real-Time SDK.
• Allows applications to achieve the highest throughput, lowest latency, low memory utilization, and low CPU utilization
• Available in C and Java flavours.

Language choice

If outright performance is not the overriding factor, then you have several choices available in terms of language and API/Library choice.

If you can code in Java or C++, the Enterprise Message API(EMA) is probably the best choice as an:

• Open source, data-neutral, multi-threaded, ease-of-use API (a wrapper around ETA)
• Offering a High Level of performance suitable for 95% of usage scenarios

However, if your language of choice is .NET, Python, Typescript then you have the following options:

• Websocket API – raw standard Websocket based interface to streaming data
• Refinitiv Data (RD) Library – high-level ease of use wrapper for the Websocket API

If you are wondering why you may use the RD library over the raw Websocket; the library takes care of various administrative tasks including login, authentication and connection management.
NOTES regarding RD Library:

• Whilst alpha versions of  Python and .NET RDP Library are still available, they have been redesigned and renamed to RD Library
• Beta versions of RD Library are now available in Python and .NET flavours
• Typescript version of the RD Library should be available end of Q1 of 2022

For any other languages that support standard Websocket creation and JSON data parsing, you can use the above mentioned raw Websocket API.

Whilst using the Websocket API requires the developer to handle things like login, connection handling & item recovery etc - we do provide basic examples in several languages demonstrating these techniques.

Performance comparison with legacy APIs

_* performance achievable with Websocket API would depend considerably on the programming language, Websocket library used etc.

Data Formats

Both the Enterprise Transport and Message API use our Open Message Model (OMM) at the application level and the binary Refinitiv Wire Format (RWF) at the transport level.

OMM provides data building blocks, a bit like ‘Lego’ but for data and you can use the ‘Lego’ to build rich data models to represent things like Full-depth order books or Yield curve data. This contrasts with the flat ‘Field-Value’ pair representation used by our legacy APIs.

RWF uses binary encoding to optimize network distribution – reduced message sizes leads to an increase in total throughput and a decrease in overall latency. Again, this contrasts with the delimited ASCII based representation used by the legacy MarketFeed format.

The Websocket API and the RDP Library use the human-readable JSON format for outgoing requests and incoming response messages.

Connectivity

In terms of connectivity, all the above APIs/libraries will allow you to consume streaming data from our cloud-based Real-time services (such as Real-Time Optimized) and your deployed Refinitiv Real-Time Distribution System (formerly known as TREP).

Additionally, the RD library will also allow you to connect to an instance of the Eikon or Workspace application running on the same PC.

Data Contribution

If you wish to implement perform Contributions (also known as Inserting/Posting) in your application, the following choices are currently available:

All three of the above APIs will allow you to Contribute data via your deployed ADS server or directly & securely over the internet to the Refinitiv Contribution Channel.

Data Publication

*^{Coming soon}

Next Steps / Additional Reading

Once you have narrowed down your choice of API - please refer to the additional articles and links to tutorials etc on the upper right-hand side of the article.

If you are concerned about the performance characteristics and whether a particular API will meet your requirements, the best option is to run some performance tests in your own environment using your own typical data universe - to get an indication of what you can expect in terms of real-life performance. 

The RT-SDK includes source code for performance test utilities - for both ETA and EMA located in the PerfTools folder of each API. Using these examples as a basis for any testing you wish to perform should make any such task easier.

For the Websocket API, you may find my Python Websocket TestClient example useful - as a starting point for any test script you wish to create. There is also a similar example for the RDP Python library.

Testing with Docker Images / AWS EC2
You will also note from the above links panel that we have made available Docker Images for RT-SDK and Websocket API. In addition to this, we also provide an AWS AMI containing the RT-SDKs and Websocket API. Hopefully, this should make it easier for you to experiment with the various APIs.

Conclusion

As the article outlines, we have a range of APIs which can be used for real-time streaming data and the exact one you choose will depend on various factors - which I hope I have covered in this article. However, if you do need further guidance, feel free to post your query/concerns on our Developer Forum and/or reach out to your Refinitiv Account representative to arrange a further discussion.