Nasdaq Pushes Market Data Onto Blockchain Rails in Distribution Expansion

The exchange operator plans to distribute its TotalView data feed via Pyth’s marketplace, as more financial institutions develop applications on blockchain-based infrastructure.

Nasdaq is broadening the reach of its market data into blockchain ecosystems by making one of its flagship equity data products available through the Pyth Network. This move comes as financial firms increasingly build trading and settlement systems on blockchain rails.

On Tuesday, the exchange announced it will deliver its TotalView market data through the Pyth Data Marketplace, a platform designed to supply institutional-grade datasets to blockchain networks, financial applications, and developers. This initiative allows a broader audience to access one of Nasdaq’s core data offerings through a programmable interface, moving beyond traditional distribution channels.

TotalView delivers full depth-of-book information, displaying buy and sell orders across all price levels for securities traded on Nasdaq, including stocks listed on Nasdaq, NYSE, and regional exchanges. It also features Nasdaq’s Net Order Imbalance Indicator, which provides real-time insights into buy and sell imbalances ahead of opening and closing auctions.

Through this collaboration, Nasdaq is extending how its market data is delivered as financial infrastructure shifts from conventional trading terminals and dedicated feeds toward cloud-based platforms and blockchain-driven applications.

The development highlights a wider trend among traditional financial institutions seeking to align market infrastructure with tokenized assets and on-chain financial services. Nasdaq joins a growing list of organizations contributing data to the Pyth Data Marketplace, including Tradeweb, SGX, OTC Markets, Kalshi, and the U.S. Department of Commerce.

According to Pyth, both developers and institutional users will be able to leverage TotalView data to assess market depth, enhance trade execution, and develop quantitative trading strategies.