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

Data Platform Modernisation: Why The Hardest Problems Are No Longer Technical

Capital markets firms pursuing data platform modernisation have largely solved the technical challenges of compute and storage, but the organisational, governance and architectural decisions surrounding those platforms remain stubbornly difficult, according to practitioners from Northern Trust, RBC Wealth Management and LSEG, speaking at a recent A-Team Group webinar entitled Data platform modernisation: Best practice approaches...

EVENT

TEST Event page 2

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

AI in Capital Markets Handbook 2026

AI adoption in capital markets has moved into a more disciplined phase. The priority is now controlled deployment: where AI can be used safely, where it can deliver measurable value, and how outputs can be governed, monitored and evidenced. The 2026 edition of the AI in Capital Markets Handbook examines how AI is being applied...