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Databento Docs

Databento provides live and historical market data. Key features include:

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Simple. A very small API surface and simple protocols. Anyone can get started in as little as 3 minutes.

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Universal. Cover multiple asset classes and venues with a single, unified message format.

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Lightweight. Full venue feeds losslessly compressed to fit over a regular internet connection.

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Easy to manage. Manage team permissions and shared licenses for your team on our platform.

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Institutional standards. Powered by the same direct feeds and PTP timestamping practices used by top financial institutions.

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No usage limits. Listen to every order book message or hundreds of thousands of symbols at once.

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Low-latency without data loss. 6.1-microsecond normalization latency. Practically zero data gaps with our FPGA-based capture.

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Flexible pricing. Pay for what you use usage-based pricing. Or get unlimited access with flat-rate pricing.

Quickstart

Build your first application

Set up your API key.
Choose from multiple APIs or install our client libraries for your language.
Get historical data in 4 lines of code.
Get live data in 6 lines of code.

View guide

New user guides

List of supported schemas Introduction to symbology Interpreting our data DBN files and encoding

View all new user guides ->

How to use your portal

Invite your teammate Team

Download flat files Download center

Start a live license agreement Licensing

Customize data selection and get pricing Data catalog

View all portal guides ->

API reference

Specifications of our Raw and HTTP APIs, as well as our client libraries (C++, Python, and Rust).

Historical data

Access historical data older than 24 hours.

Live data

Access real-time and intraday data from within the last 24 hours.

Examples by use case

Basics

Basic usage of Databento for new users

Handling a large number of symbols (Historical) Getting midprice, BBO and log returns Portfolio benchmarks Technical indicators

Order book

Market-by-order (MBO) and market-by-price (MBP)

Limit order book construction Microprice, book imbalance, and book pressure Using queue position

Instrument definitions

Instrument properties and symbology

Finding liquid instruments Handling tick sizes

Algorithmic trading

Alpha research, execution, and simulation

Building prediction models with machine learning Execution slippage and markouts Measuring matching engine and feed latency Messaging rates and implied volatility