OptionMetrics, one of the best-known providers of historical options data used by institutional investors and academic researchers, has made its datasets available through Snowflake’s private cloud marketplace, reflecting a broader shift in capital markets away from locally stored market data and toward cloud-native research infrastructure.
The move allows firms with Snowflake environments to access OptionMetrics’ historical and intraday options datasets directly from the cloud, eliminating the need to download and maintain large local databases. While the announcement is primarily a distribution expansion rather than a new dataset, it highlights how the competitive battleground in financial data is increasingly shifting from the quality of information alone to how quickly quantitative researchers, traders and risk managers can access and analyze it.
For institutional investors, market data has become as much an infrastructure challenge as an information challenge. Modern quantitative strategies increasingly combine options, equities, futures, fixed income and alternative datasets, requiring platforms that can process enormous volumes of historical information without firms maintaining their own storage infrastructure. As FinanceFeeds recently reported, institutional firms are also seeking greater consolidation across execution and risk management systems, illustrating a wider industry trend toward integrated technology stacks rather than disconnected data silos.
Cloud Delivery Is Changing Market Data Distribution
Historically, financial data vendors distributed large datasets through downloadable files that customers stored and managed on their own servers. While that model remains common, it has become increasingly expensive as quantitative research has expanded to include decades of tick data, derivatives pricing, volatility surfaces and alternative datasets.
Cloud marketplaces are changing that model by allowing customers to query datasets directly where they reside instead of maintaining local copies. For researchers, this reduces storage costs and infrastructure management while allowing multiple teams to work against the same continuously updated dataset.
OptionMetrics said clients can continue downloading data traditionally but now also have the option of accessing datasets directly through their Snowflake environments. The company will maintain and update the datasets on an ongoing basis so users always query current versions rather than periodically refreshing local databases.
“With today’s fast-moving markets, more seamless access to options data can give risk managers and quantitative professionals an edge as they assess trading strategies,” said Eran Steinberg, Chief Operating Officer of OptionMetrics.
“In making our data accessible via the cloud with Snowflake, we are giving institutional investors and academic researchers a convenient way to quickly access the options data and analytics they rely on daily.”
A Core Dataset for Quantitative Finance
OptionMetrics has long been regarded as one of the standard reference datasets for options research in both the investment industry and academia. Its IvyDB databases are widely used to study volatility, derivatives pricing, options market structure, portfolio risk and systematic trading strategies.
The datasets now available through Snowflake include the company’s flagship IvyDB US historical end-of-day database alongside its intraday US options dataset, which captures market snapshots throughout the trading day at 10:00 a.m., 2:00 p.m. and 3:45 p.m. Eastern Time.
The marketplace also includes regional datasets covering Europe, Canada and Asia-Pacific, global index options and futures options traded across North American and European exchanges.
Together, those products provide researchers with historical implied volatility, option prices, Greeks and other derivatives analytics used to backtest trading strategies, evaluate portfolio risk and conduct empirical market research.
Demand for those capabilities has grown as options markets have become increasingly central to institutional portfolio management. The rapid expansion of listed options volumes, the rise of retail options trading and growing institutional use of volatility strategies have increased demand for clean, standardized historical datasets capable of supporting sophisticated quantitative models.
Cloud Infrastructure Is Becoming Part of Trading Infrastructure
The announcement also reflects how cloud computing has become embedded within financial market infrastructure.
Rather than simply hosting applications remotely, cloud providers increasingly serve as marketplaces where financial institutions discover, purchase and consume commercial datasets without separate delivery arrangements. That reduces integration work while allowing firms to combine multiple vendors’ datasets inside common analytics environments.
Snowflake has emerged as one of the largest participants in that trend, positioning itself not simply as a cloud database provider but as what it describes as an AI Data Cloud, allowing enterprises to share data, applications and increasingly artificial intelligence models through a common platform.
The growing role of cloud-native infrastructure extends beyond market data. FinanceFeeds recently covered the wider institutional technology shift toward centralized analytics and execution infrastructure, while TS Imagine’s integration of prediction market data into institutional risk systems illustrates how investment firms increasingly expect diverse datasets to be consumed through unified technology environments rather than isolated applications.
For quantitative researchers, cloud-native access also supports increasingly collaborative workflows. Data scientists, portfolio managers and risk teams can query the same datasets simultaneously without duplicating storage or maintaining separate research environments.
Infrastructure Is Becoming a Competitive Differentiator
Making datasets available through Snowflake is unlikely to change the underlying information itself, but it changes how quickly institutions can put that information to work. As quantitative investing becomes increasingly data-intensive, accessibility has become a competitive advantage alongside coverage, quality and historical depth.
That is particularly relevant for derivatives research, where backtesting often requires processing millions of historical option contracts across multiple markets. Running those analyses directly in cloud infrastructure can reduce both capital expenditure and operational complexity for investment firms.
The move also reflects broader competitive dynamics among financial data vendors. Increasingly, providers are expected not only to produce proprietary datasets but also to integrate them into the technology ecosystems already used by institutional clients. Distribution through cloud marketplaces therefore becomes another way of reducing friction between acquiring data and generating investment insight.
Clients will still require a Snowflake licence to access the datasets through the platform, but for firms already operating cloud-native research environments, OptionMetrics’ latest distribution channel removes another layer of infrastructure from the research process. As institutional investing continues shifting toward cloud-based analytics, vendors that deliver both high-quality data and seamless integration are likely to hold an increasingly important position in quantitative finance.
