About a-team Marketing Services
The knowledge platform for the financial technology industry
The knowledge platform for the financial technology industry

A-Team Insight Blogs

Latency – All About A, B and C (for Compute)

Subscribe to our newsletter

I often describe latency as the time it takes to move data from point A to point B, and/or the time taken to process that data at points A and B. I think it’s true to say that the majority of content on this site is about moving data from A to B. But processing data – the C, or compute element, of latency is increasingly a focus.

The computing in low latency processing takes many forms.  It can be related to data manipulation, such as the conversion of message formats; or data management, such as working with a time series database; or numerical processing, such a calculating an order price or size.

With the latency related to moving data – propagation latency – well understood, increasingly a focus for architects and developers is the latency related to trading applications, and minimising this compute element is very much the goal of this activity.

Tackling this application latency is very much a requirement for “Intelligent Trading” – making the right trade in a timely manner, though not always being the fastest.

Reducing application latency is not just about software. The hardware platform upon which applications run play a crucial role, even though the software geeks often wince at solving a challenge through faster hardware.

As an example, recent news from DataDirect Networks related to its STAC-M3 benchmark, involving processing of tick histories managed by Kx Systems’ kdb+ database running against its SFA12K-40 hybrid flash/spinning disk ‘Big Data’ platform, demonstrates the role of hardware in directly boosting application performance.

We’ll be covering this topic increasingly within the Low-Latency.com community. It will also be a big focus on our May 1 Low-Latency Summit, taking place in New York City.

Subscribe to our newsletter

Related content

WEBINAR

Recorded Webinar: Data platform modernisation: Best practice approaches for unifying data, real time data and automated processing

Financial institutions are evolving their data platform modernisation programmes, moving beyond data-for-cloud capabilities and increasingly towards artificial intelligence-readiness. This has shifted the data management focus in the direction of data unification, real-time delivery and automated governance. The drivers of this transition are improved operational efficiency as manual processes are replaced by faster, more accurate automated...

BLOG

xyt Layers Natural-Language AI onto Trading Data Platform as Race for AI-Ready Analytics Intensifies

xyt, the independent trading data intelligence platform formerly known as big xyt, has introduced a set of AI-powered capabilities designed to let clients query its datasets in natural language, integrate its data into their own AI environments, and generate executable analytical outputs from a prompt. The announcement positions the firm in an increasingly crowded field...

EVENT

TEST Event page 1

Now in its 15th year the TradingTech Summit London brings together the European trading technology capital markets industry and examines the latest changes and innovations in trading technology and explores how technology is being deployed to create an edge in sell side and buy side capital markets financial institutions.

GUIDE

Entity Data Management

Entity data management has historically been a rather overlooked area of the reference data landscape, but with the increase focus on managing risk, the industry is finally taking notice. It is now generally agreed to be critical to every financial institution; although the rewards for investment in entity data management appear to be rather small,...