The leading knowledge platform for the financial technology industry
The leading knowledge platform for the financial technology industry

A-Team Insight Blogs

Refinitiv Launches Tick History in Google Cloud to Speed Access and Lower Storage Costs

Refinitiv has made its archive of historical pricing and trade data – five petabytes’ worth of information – available to clients via the Google Cloud Platform (GCP). The offering will allow customers will also be able to access, query and analyse Refinitiv’s tick data using the machine learning capabilities of Google Cloud’s BigQuery.

The move builds on Refinitiv’s strategy of making data available in the cloud to support specific use cases, and follows an industry-wide trend towards enabling the use of large data sets and associated analytics in cloud environments.

A 2019 global Refinitiv survey of 300 senior executives and heads of market data noted that “as cloud adoption in financial services evolves, companies are finding that the benefits are not just about cost efficiencies but also to do with resilience, agility and innovation.” The survey also found that 64% of firms believe that cloud use will be “significant, or transformational, for their sector over the next five to 10 years..

Refinitiv offers other Cloud-based products, including QA Direct in the Cloud, a quantitative analytics platform delivered through Microsoft Azure. A year ago, Refinitiv also announced that it had selected Influx DB to help it develop additional cloud-based time-series analytics services. This initiative was part of a wider shift to deliver Refinitiv services, including real-time and other data, in a service-oriented cloud-based platform requiring minimal client-side equipment or maintenance.

Moving to the Cloud

Refinitiv’s tick history data set is drawn from real-time content and covers over-the-counter (OTC) and exchange-traded instruments from all asset classes traded on more than 500 venues and dating back to 1996. “The idea developed while working with customers who were looking to solve two real problems,” says Gavin Carey, now head of enterprise in EMEA at Refinitiv and previously responsible for the company’s tick history business. “One was the time it takes to get the volumes of data that we’re looking at, with tick history, from Refinitiv to our customers. And the second being the cost that our customers each incur when storing these large volumes of data.”

The move to the cloud enables customers to work across large data sets remotely and in a fraction of the time that they would typically experience, according to the company. Customers using the solution are also likely to enjoy a lower total cost of ownership, as they benefit from a reduced infrastructure spend and storage required to maintain and integrate the scale of Refinitiv’s tick history data on-premise, according to Refinitiv.

In addition, customers can perform analytics using BigQuery – to build and back-test trading strategies, perform quantitative research and analysis while minimizing slippage, and meet regulatory and best execution requirements, says Catalina Vazquez, proposition director of tick history at Refinitiv. The solution also supports quants and data scientists who want to apply machine learning and artificial intelligence processes to the data.

“The way that things would work before, the customer would have to access our surveys, download a file, manage that and store it on-site. It would have to allocate storage, compute, and also people resource, to be able to manage this process,” says Vazquez. “Whereas today, all you need to do is set up your instance in Google and you’re ready to query our Refinitiv-managed data set. It reduces timelines around the workflow, but it also helps them address the challenges around the volume and the under storage and computes.”

When looking to develop future cloud-based solutions, “We don’t just look at migrating a capability to meet our customers’ needs,” says Nathan Attrell, director of cloud proposition at Refinitiv. “We’re not merely lifting and shifting. Every time that we’re embarking on making content available in the cloud, we’re looking to transform it, to improve the service offering to our customers. We’re taking the correct content sets into specific environments, that are closely aligned to customer workflows. BigQuery and GCP is a good one because there’s a lot of gravity towards that, from a lot of quants and data scientists.”

Related content


Recorded Webinar: The evolution of market surveillance across sell-side and buy-side firms

Market surveillance is crucial, and in many cases a regulatory requirement, to ensuring orderly securities markets and sustaining confidence in trading. It can be breached and has become increasingly complex in the wake of the Covid pandemic, Brexit, and the emergence of new asset classes. This webinar will review the extent of market abuse in...


Intelligent Machine Readable News – How to Get a Signal from the Noise

Intelligent machine readable news is a powerful tool in the arsenal of trading firms seeking competitive advantage. It offers opportunities to turn unstructured data into actionable insight that can be used to uncover market trends, identify correlations and evaluate sentiment, but also raises challenges such as information sourcing, timing and contextualisation. A recent A-Team Group...


Data Management Summit London

Now in its 12th year, the Data Management Summit (DMS) in London brings together the European capital markets enterprise data management community, to explore the evolution of data strategy and how to leverage data to drive compliance and business insight.


Trading Regulations Handbook 2021

In these unprecedented times, a carefully crafted trading infrastructure is crucial for capital markets participants. Yet, the impact of trading regulations on infrastructure can be difficult to manage. The Trading Regulations Handbook 2021 can help. It provides all the essentials you need to know about regulations impacting trading operations, data and technology. A-Team Group’s Trading...