Databento raises $97 million Series B as profitable market data startup expands globally

Christina Qi’s company provides low-latency market data across more than 60 venues, including crypto futures, as it scales infrastructure after drawing over $300 million in demand for the round.

Summary

Databento has raised a $97 million Series B led by NEA, with participation from DRW Venture Capital, Redpoint Ventures, and Tribe Capital, adding to roughly $127 million in total disclosed funding after earlier rounds of about $37.5 million. The market data infrastructure company, founded by Christina Qi after she shut down Domeyard LP, said the round attracted more than $300 million in demand. The company says it is already profitable with 24 employees and now serves more than 3,000 firms. Databento provides low-latency APIs for real-time and historical market data across equities, futures, options and other asset classes from more than 60 trading venues, with tick-by-tick trades and full order books available through Python, Rust and C++. The funding is earmarked for infrastructure expansion. Databento plans to grow from servers housed inside stock exchanges to more than 20 data centers worldwide and has secured more than 100 additional petabytes of storage, more than doubling its earlier footprint. Its crypto exposure is broader than a traditional market-data label suggests. Databento already includes cryptocurrency futures data from CME and CFE, made CFE PCAPs for volatility and crypto futures available on the platform in October 2025, and has outlined plans to add Binance spot, futures and options data. The company has also partnered with NautilusTrader to support workflows spanning traditional finance and crypto trading in one environment.

Terms & Concepts
  • low-latency APIs: Data interfaces designed to deliver information with minimal delay, which is critical for trading systems.
  • full order books: Detailed market data showing all active buy and sell orders, not just completed trades.
  • PCAPs: Packet-capture files that preserve raw network data feeds for detailed analysis and replay.