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

NYSE Technologies Looks to Open Source Data APIs; Wants Competitors To Partner

Subscribe to our newsletter

NYSE Technologies is planning to open source its messaging APIs, and hopes to attract other market participants – and competing data providers – to adopt them. The plan was outlined by Tony McManus, head of Enterprise Software at the exchange’s technology unit, speaking at a recent FutureDATA event in London.

The APIs in question are NYSE Technologies’ Middleware Agnostic Messaging API (MAMA) and the Middleware Agnostic Market Data API (MAMDA). Along with those, a data model is being created to allow applications to make sense of the data payloads. McManus noted the goal is to make the APIs and data model an industry standard.

McManus noted that NYSE Technologies is in dialog with its “hardest competitors” to pursuade them to partner on the initiative. Noting that the open source move is one away from being “proprietary and protectionist” and also “a risky strategy,” McManus said the company’s belief is that its innovation in technology will give it a leading position in what will be an larger marketplace for data services.

That marketplace is one for enterprise data as a whole, as opposed to a narrower one for ultra low-latency trading applications. As such, latency is just one factor being considered by customers. Others include ease of integration, data coverage, avoiding vendor lock-in, and cost.

In that respect, NYSE Technologies expects its Data Fabric messaging middleware – especially its recently-release 6.0 release – will prove formidable because of its performance, scalabilty and support of different data transports.

Open sourcing of data APIs is not new, though they are somewhat in vogue at present. Bloomberg is one market data vendor making noises about providing open source APIs. Also, the Open Market Data Initiative – which has been supported by Bank of America Merrill Lynch – has defined an API (MDAL – for Market Data Abstraction Layer) and has developed a number of direct market data feeds that support it.

Subscribe to our newsletter

Related content

WEBINAR

Recorded Webinar: Navigating the Build vs Buy Dilemma: Cloud Strategies for Accelerating Quantitative Research

For many quantitative trading firms and asset managers, building a self-provisioned historical market data environment remains one of the most time-consuming and resource-intensive steps in establishing a new research capability. Sourcing data, normalising symbologies, handling corporate actions and maintaining infrastructure can take months and absorb significant budget before a single model is tested. At the...

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

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...