Databento, a developer-focused market data platform, closed a $97 million Series B round led by New Enterprise Associates to expand its infrastructure, scale into global markets, and integrate digital asset coverage.
Databento raised $97 million in an oversubscribed Series B round, led by New Enterprise Associates (NEA), with participation from DRW Venture Capital, Redpoint Ventures, Tribe Capital, and other strategic and existing investors including Alumni Ventures, Blindspot Ventures, Cross Creek, Fifth Down Capital, Motley Fool Ventures, Operator Collective, TGVP, and Trousdale Ventures.
The round drew over $300 million in demand, reflecting strong investor enthusiasm. It brings Databento’s total disclosed funding to approximately $127 million since its 2019 founding. Rick Yang (Partner and Head of Technology at NEA) joined the board, with Danielle Lay (NEA Partner) as a board observer.
What is Databento?
Databento, headquartered in Salt Lake City, Utah, provides a modern, API-first market data platform offering real time, historical, and reference data directly from colocation facilities (e.g., NY4, FR2, Aurora I). It supports major asset classes including futures, options on futures, equities, equity options (covering venues like CME, Eurex, ICE, and all 18 US equity options exchanges), with spot FX planned.
Key differentiators include:
- Usage based pricing (pay only for data used) alongside flat rate options, with low historical costs (e.g., from $0.50/GB) and efficient delivery.
- High performance infrastructure: Nanosecond/PTP timestamps, full order book (L3/mbo, mbp-10, etc.), schemas for trades, OHLCV, statistics; binary DBN encoding; low latency (median ~590 μs over internet); raw PCAPs.
- Ease of use: Client libraries (Python, Rust, C++), Pandas optimization (>1M rows/sec), self-service portal, and minimal code to integrate (e.g., 4 lines for historical replay).
- Direct sourcing: No intermediaries, from exchange feeds, with normalized yet high fidelity data.
The company targets a broad customer base, from individual developers and students (free credits available) to hedge funds, prop trading firms, broker dealers, fintechs, commodities traders, digital asset firms, and AI labs (e.g., Nvidia, OpenAI). It claims over 3,000 companies, with thousands to tens of thousands of users, and products powering retail trading apps and physical commodities flows.
Founded by ex quants and traders (CEO Christina Qi from Domeyard/UBS/Goldman; team from Two Sigma, Flow Traders, Tower Research, etc.), Databento emphasizes solving operational pain points in production workflows rather than just data access. It operates leanly with under 30 employees (often cited around 24), enabling rapid iteration.
Databento demonstrates exceptional traction:
- Revenue growth: 6.65x year over year (as of the announcement). Earlier periods showed 985% surge, 4.2x GAAP increases, and strong quarterly/MoM gains (e.g., 84% q/q, 23% MoM in prior reports). It reached profitability monthly well ahead of schedule without burning prior capital.
- Retention: 97% enterprise retention since inception.
- Scale: Serves >20 PB raw data (expanding to >100 PB storage), 650k+ symbols on CME alone, historical data back to 2010+, 70+ exchange feed handlers, 60+ venues, and global users. High enterprise mix (much of ARR from large firms with trillions in AUM/trading volume).
- Efficiency: Lean team with high output; positioned as one of fintech’s fastest growers, with customers spanning the spectrum of finance and AI.
This positions it as a challenger to legacy providers like Bloomberg terminals and Refinitiv (LSEG), capitalizing on the shift to programmatic/API driven data access in an industry spending >$50B annually on market data.
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How will Databento use the funds?
Funds will accelerate global expansion:
- New data centers (target: >20 worldwide in ~6 months), focusing on Europe and APAC.
- Storage scaling (>100 PB usable capacity).
- Coverage for additional asset classes and geographies.
- Infrastructure enhancements to maintain technical leadership (low latency, high throughput, reliability).
This builds on prior momentum, including live data launches, new datasets (e.g., corporate actions), and subscription model refinements.
The market data sector is ripe for disruption. Legacy systems often involve high fixed costs, complex integrations, vendor lock-in, and terminals ill-suited for modern programmatic, cloud native, and AI/ML workflows. Databento’s cloud friendly full depth feeds, flexible pricing, and developer focus address these, enabling faster “idea to production” cycles.
Strong demand from sophisticated users (hedge funds, prop shops, AI labs) validates the product market fit. Oversubscription and participation from industry players (e.g., DRW) signal confidence. Valuation details are not publicly confirmed in announcements, but the round size and growth imply a significant step-up from earlier stages.
Challenges include regulatory/licensing hurdles for data distribution, competition from incumbents and other fintechs, execution on global expansion, and sustaining high growth/profitability amid infrastructure costs. However, the team’s domain expertise, proven metrics, and capital position it favorably.
The $97M Series B underscores Databento’s rapid ascent as a high efficiency leader in modern market data infrastructure. It reinforces the thesis that API centric, cost effective, high fidelity solutions are winning share in a digitizing finance ecosystem, setting the stage for broader adoption across trading, research, and AI applications. The company is well capitalized to scale infrastructure and coverage while maintaining its lean, profitable trajectory.
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