{
  "slug": "databento",
  "name": "Databento",
  "aliases": [],
  "vendor": { "name": "Databento, Inc.", "slug": "databento", "website": "https://databento.com" },
  "homepage_url": "https://databento.com/",
  "docs_url": "https://databento.com/docs",
  "repo_url": "https://github.com/databento/databento-python",
  "pricing_url": "https://databento.com/pricing",
  "product_type": "api-service",
  "product_status": "active",
  "summary": "Usage-priced market data platform with normalized order-book (MBO/MBP), trades, OHLCV and reference schemas for futures, options and equities, delivered via historical, live and batch APIs in the DBN format",
  "description": "Databento is a market data vendor built around a single normalized data model. Every dataset, whether CME Group futures and options, OPRA equity options, Nasdaq TotalView-ITCH, Eurex, ICE or Databento's own consolidated US equities feed, is published in the same set of schemas: market-by-order (full L3 book), market-by-price at one or ten levels, trades, top-of-book, OHLCV bars from one second to daily, statistics, instrument definitions, imbalances, status, and reference data such as corporate actions, adjustment factors and a security master. Data are encoded in Databento Binary Encoding (DBN), an open, Zstandard-compressed format with Apache-2.0 decoders, and can be converted to CSV, JSON or Parquet.\n\nThree APIs share the model: a Historical API with time-series range requests, batch downloads, symbology resolution and cost estimation; a Live API that streams real-time data with intraday replay and snapshots; and a Reference API for corporate actions and security master. Official clients exist for Python, C++ and Rust alongside raw HTTP and TCP interfaces.\n\nPricing is unusual among vendors: historical data are pay-as-you-go metered by data volume, with signup credits, optional flat-rate subscriptions for individuals and teams, and annual institutional tiers. Live data require a venue licence; Databento acts as vendor of record, passes exchange fees through without markup and distinguishes display from non-display and internal from external use, with redistribution of real-time and intraday data governed per venue. Historical bars for research can therefore be bought incrementally, but order-book-scale downloads for many symbols and years become costly, the catalog is concentrated on US and European derivatives and US equities, and the DBN toolchain is a learning step compared with plain CSV.",
  "capabilities": ["Normalized schemas: MBO, MBP-1, MBP-10, trades, TBBO, OHLCV, statistics, definitions", "Historical API with range requests, batch downloads and cost estimates", "Live streaming API with intraday replay and snapshots", "Reference API for corporate actions, adjustment factors and security master", "DBN open binary encoding with CSV, JSON and Parquet conversion", "Official Python, C++ and Rust clients plus raw HTTP/TCP", "Venues: CME Group, OPRA, Nasdaq ITCH, Eurex, ICE, Databento US Equities", "Vendor-of-record licensing for live data"],
  "workflows": ["Reconstructing the limit order book from MBO data for microstructure research", "Minute bars for a universe of futures bought incrementally by volume", "Live replay of a trading session for strategy testing", "Converting DBN files to Parquet for DuckDB analysis"],
  "advantages": ["One schema set across all venues", "Pay-for-what-you-use historical pricing", "Open DBN format and open-source clients", "Full-depth order-book data"],
  "limitations": ["Order-book downloads at scale are expensive", "Live data need venue licences and fee pass-through", "Coverage concentrated on US/European derivatives and US equities", "DBN tooling has a learning curve versus CSV"],
  "prerequisites": ["Account and API key", "Python, C++ or Rust client or HTTP"],
  "audiences": ["Market-microstructure researchers", "Systematic traders needing order-book data", "Data engineers building tick databases"],
  "alternatives": ["polygon-io", "firstrate-data", "wrds", "interactive-brokers-api", "bloomberg-terminal"],
  "comparison_notes": "Massive (formerly Polygon.io) sells subscription API access centred on US equities and options with flat files; FirstRate Data sells perpetual-licence CSV bundles without order-book depth; WRDS provides TAQ to subscribing institutions through SQL. Databento's distinguishing features are metered pricing, L3 order-book schemas and the open DBN format.",
  "categories": [{ "slug": "market-data-apis", "primary": true }, { "slug": "hf-finance-research" }],
  "tags": ["market-data", "order-book", "time-series", "api", "futures", "options", "parquet"],
  "use_cases": ["analyze-intraday-data", "access-market-data", "query-parquet-files"],
  "operating_systems": ["any"],
  "execution_modes": ["cloud"],
  "interfaces": ["api", "sdk", "web"],
  "deployment_models": ["saas"],
  "integrations": ["Python client", "C++ client", "Rust client", "pandas", "Parquet", "Zstandard"],
  "data_formats": ["DBN", "CSV", "JSON", "Parquet"],
  "languages": ["Python", "C++", "Rust"],
  "source_model": "mixed",
  "pricing_model": ["usage-based", "paid", "enterprise"],
  "pricing_checked_at": "2026-11-02",
  "self_hostable": false,
  "sources": [
    { "url": "https://databento.com/", "type": "official_site", "title": "Databento", "supports": ["name", "summary"], "checked_at": "2026-11-02" },
    { "url": "https://databento.com/docs", "type": "official_docs", "title": "Databento API documentation", "supports": ["capabilities", "data_formats", "languages", "interfaces"], "checked_at": "2026-11-02" },
    { "url": "https://databento.com/pricing", "type": "pricing_page", "title": "Databento pricing", "supports": ["pricing_model", "description", "capabilities"], "checked_at": "2026-11-02", "note": "Usage-based historical pricing, subscriptions, exchange fee pass-through" },
    { "url": "https://databento.com/docs/portal/live-data", "type": "policy_page", "title": "Live data licensing", "supports": ["limitations", "description"], "checked_at": "2026-11-02", "note": "Display vs non-display, internal vs external use, vendor of record" },
    { "url": "https://github.com/databento/databento-python", "type": "repository", "title": "databento/databento-python", "supports": ["repo_url", "source_model"], "checked_at": "2026-11-02", "note": "Apache-2.0 client library; the data service itself is proprietary" }
  ],
  "confidence": "high",
  "uncertainty_note": "The legal terms page renders client-side and could not be read by automated tools; licensing statements are taken from the pricing page and the live-data documentation. source_model 'mixed' reflects open-source clients and DBN decoders around a proprietary service.",
  "discovery_method": "editorial-research",
  "depth": "deep",
  "editorial_status": "reviewed",
  "visibility": "public",
  "featured": false,
  "author": "batch-E"
}