Comprehensive market coverage
Select and customize data down to the symbol. Choose your favorite format, encoding, and delivery.
AUM of hedge funds whose researchers use Databento
emerging managers and CTAs over $100M AUM
developers at tech startups valued over $1B
The most powerful API for normalized market data
Brought to you by the same engineers behind market data infrastructure at some of the world’s leading HFT firms
Entire venue in a single API call
Fetch all symbols on the venue in one call. Like a direct feed. Even over internet.
Precision timestamping with PTP
Up to 4 timestamps per event, in nanosecond resolution.
Optimized for Pandas dataframes
Get market data in dataframes at over a million rows per second.
Select symbols, format, encoding, and delivery. Get any range by the nanosecond.
Blazing fast market replay of full order book data
Replay events in the same order as our live APIs. Use the same code between historical and live data.
Batch download with a single click
Quickly select different schemas and time ranges with a single click.
Preview sample data
Extract sample data in various formats within seconds in your web browser.
Modern features built for top financial institutions
Skip the sales call. Access your first dataset in as little as 3 minutes.
Direct from colocation facilities
Sourced and distributed straight from the colocation facilities that house each venue’s matching engine.
Cover multiple asset classes and trading venues with one unified message format.
Choose between CSV, JSON, and our highly-compressed binary encoding, DBN.
Multiple symbology systems
Continuous contracts, options chains, rollover rules, venue-native numeric IDs, ticker symbols, and more.
Scale up with near-unlimited API calls and enough bandwidth even for a full-venue firehose.
Build your first application in 4 lines of code
Databento works with any language through our Raw API, which uses a binary protocol over TCP, and our HTTP API. We also provide client libraries for Rust, Python, and C++.
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import databento as db client = db.Historical('YOUR_API_KEY') data = client.timeseries.get_range( dataset='GLBX.MDP3', schema='mbo', start='2023-01-09T00:00', end='2023-01-09T20:00', limit=100, ) data.replay(print)
Reference – Historical
Reference – Live
Flexible pricing to meet your needs
Only pay for the data you use with usage-based pricing, or get unlimited data with our flat-rate pricing. Skip the sales call and get an instant price quote today.See pricing