LSEG significantly accelerates analysis of years of Tick History market data with NVIDIA cuDF

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Benchmark analysis shows years of LSEG Tick History can be analysed in seconds using NVIDIA cuDF for GPU-accelerated data processing, reducing processing time from hours to…

LONDON - LSEG today announced a collaboration with NVIDIA to help financial institutions analyse large volumes of LSEG Tick History data at significantly greater speed and scale using NVIDIA cuDF for accelerated computing on NVIDIA GPUs. This is achieved without creating another full copy of the underlying dataset while also preserving the licences, permissions and controls that govern access.

The collaboration brings LSEG’s trusted, permissioned historical market data closer to the computing environments used for quantitative research, market analysis and AI. As part of the LSEG Everywhere AI strategy, users can run large-scale data processing on Tick History datasets to turn LSEG content into insights faster.

Benchmark analysis shows years of LSEG Tick History can be analysed in seconds using NVIDIA cuDF and Polars, reducing processing time from hours to seconds. As equity trading moves towards near 24-hour operation, firms are moving away from legacy models that rely on market-close data loading and overnight analytics. This capability enables deeper, continuous historical analysis throughout the trading day.

LSEG Tick History holds 110 trillion rows of data across 100 million instruments spanning more than 30 years and more than 580 exchanges, trading venues and contributors. In H1 2026, traffic over LSEG’s real-time network grew by 29% versus H1 2025, reaching a new peak of 26 million messages per second in June, while customer API requests for Tick History data increased by 48%.

“This collaboration expands how customers can draw insight from LSEG’s trusted, governed Tick History. Customers want to work with detailed historical data at speed, without the burden and risk of creating another full copy. This helps firms analyse deeper histories closer to the point of decision, while keeping the permissions and controls they rely on fully intact.”

“AI is opening new ways to understand market behavior across vast amounts of data.

The collaboration is intended to support…

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