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Leveraging In-Memory for Real-Time MapReduce Analytics

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See the video below on how in-memory technology from ScaleOut Software can boost MapReduce 40x for financial applications, such as real-time risk analytics.

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Related content

WEBINAR

Recorded Webinar: From Data to Alpha: AI Strategies for Taming Unstructured Data

Unstructured data and text now accounts for the majority of information flowing through financial markets organisations, spanning research content, corporate disclosures, communications, alternative data, and internal documents. While AI has created new opportunities to extract signals, many firms are discovering that value is constrained not by models, but by the quality of the content, architecture,...

BLOG

When Market Data’s Cloud Migration Is Over, What’s Left Behind?

The firms furthest along with cloud have stopped arguing about whether market data belongs there. What occupies them now are the questions that outlasted the migration: where the on-premises boundary finally holds, what turns out to cost money, and whether entitlement frameworks built for headcount can survive machines that consume data at machine speed. Getting...

EVENT

Digital Assets & Tokenisation Forum, New York

A-Team Group’s Digital Assets & Tokenisation Summit spotlights how global financial leaders are rapidly embracing programmable tokenised assets and DLT networks to achieve real-time, 24/7 peer-to-peer transactions.

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...