Nasdaq expands distribution of its market data into blockchain infrastructure
The exchange operator will offer its TotalView data feed through Pyth’s marketplace as financial firms increasingly build applications on blockchain rails.
By Helene Braun|Edited by Nikhilesh De
Jun 30, 2026, 1:00 p.m.
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Summary
Nasdaq is expanding the distribution of its market data into blockchain infrastructure, making one of its flagship equity data products available through the Pyth Network as financial firms increasingly build trading and settlement applications on blockchain rails.
The exchange operator said Tuesday it will publish its TotalView market data through the Pyth Data Marketplace, a platform that distributes institutional datasets to blockchain networks, financial applications and software developers. The move gives a wider range of users access to one of Nasdaq’s core market data offerings through a programmable interface rather than traditional market data delivery channels.
TotalView provides full depth-of-book data, showing buy and sell orders at every price level for securities trading on Nasdaq, including Nasdaq-, NYSE- and regional-listed stocks. The product also includes Nasdaq’s Net Order Imbalance Indicator, which offers a real-time view of buy and sell imbalances before the opening and closing auctions.
For Nasdaq, the partnership expands how its market data reaches customers as financial infrastructure evolves beyond trading terminals and dedicated market data feeds toward cloud-based software and blockchain-powered applications.
The announcement reflects a broader push by traditional financial institutions to make market infrastructure compatible with tokenized assets and onchain financial services. Nasdaq joins a growing roster of organizations publishing data through the Pyth Data Marketplace, including Tradeweb, SGX, OTC Markets, Kalshi and the U.S. Department of Commerce.
Pyth said developers and institutional users will be able to use TotalView data to analyze market depth, improve trade execution and build quantitative trading models.
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