databento
Official Python client library for Databento
Decision gist · record as of 2026-08-14
Yes. The package is actively maintained, has no known vulnerabilities, installs with low friction, and is licensed permissively. It is the official client for a specialized but well-established market data service. Install it if you need programmatic access to Databento's historical or live market data; skip it if you don't have a Databento account or need data from a different provider.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python >=3.10 and a valid Databento API key (free signup available); Windows users need pip-system-certs.
- Low friction installation with a pure-Python wheel.
- Active maintenance with a release 9 days old and a recent commit history.
License · maintenance · safety
Apache-2.0 (permissive) — Apache-2.0 permissive license allows commercial and private use without restriction, with minimal attribution requirements.
last release 2026-08-05 (9 days) · last repo commit 2026-08-10 · 293 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 1,745,295 downloads/mo, #3,597 on PyPI
Alternatives
Verify before relying
pip install -U databento
import databento as db
client = db.Historical('YOUR_API_KEY')
data = client.timeseries.get_range(
dataset='GLBX.MDP3',
symbols='ES.FUT',
stype_in='parent',
start='2022-06-10T14:30',
end='2022-06-10T14:40',
)
df = data.to_df()- Whether the library supports real-time streaming in addition to historical batch retrieval.
- Performance characteristics and throughput limits for large datasets or high-frequency replay.
- Whether smart symbology and point-in-time instrument definitions are available in the free tier.
What it is and what it does
Databento is the official Python client for the Databento market data platform, providing unified access to both live and historical financial data across multiple asset classes and venues. It abstracts away the complexity of different data formats and symbology systems by offering fully normalized schemas—the same message structure works for both live and historical data, whether you're working with market-by-order, market-by-price, top-of-book, OHLCV, or last-sale events. The library efficiently stores and reads data in Databento Binary Encoding format and supports event-driven market replay at any granularity, from daily bars to high-frequency order book snapshots.
The package is built on a foundation of mature dependencies: aiohttp and requests for HTTP communication, pandas and numpy for data manipulation, pyarrow for columnar storage, and zstandard for compression. It requires Python 3.10 or later and is actively maintained. You interact with it by instantiating a Historical or Live client with an API key, then calling methods like timeseries.get_range() to fetch data, which you can then replay event-by-event, convert to a pandas DataFrame, or export to CSV or JSON. The library handles API authentication, data normalization, and symbology mapping transparently.
Use it for
- Backtest trading strategies using normalized historical order book or OHLCV data with event-driven replay.
- Fetch and analyze multi-asset time series (equities, futures, options) with point-in-time instrument definitions.
- Build real-time market monitoring dashboards by consuming live feeds and converting to pandas DataFrames.
- Perform high-frequency research on order book dynamics using market-by-order schemas across multiple venues.
- Batch download and store market data in efficient binary format for offline analysis or archival.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes.
The package is actively maintained, has no known vulnerabilities, installs with low friction, and is licensed permissively. It is the official client for a specialized but well-established market data service. Install it if you need programmatic access to Databento's historical or live market data; skip it if you don't have a Databento account or need data from a different provider.
Install
databento on PyPI
Before you install
Low friction installation with a pure-Python wheel. Active maintenance with a release 9 days old and a recent commit history. Eight runtime dependencies are all widely-used libraries (aiohttp, pandas, numpy, pyarrow, requests, zstandard, databento-dbn, pip-system-certs).
Requires Python >=3.10 and a valid Databento API key (free signup available); Windows users need pip-system-certs.
License in practice
Apache-2.0 permissive license allows commercial and private use without restriction, with minimal attribution requirements.
Quickstart
pip install -U databento
import databento as db
client = db.Historical('YOUR_API_KEY')
data = client.timeseries.get_range(
dataset='GLBX.MDP3',
symbols='ES.FUT',
stype_in='parent',
start='2022-06-10T14:30',
end='2022-06-10T14:40',
)
df = data.to_df()Verify before relying
- Whether the library supports real-time streaming in addition to historical batch retrieval.
- Performance characteristics and throughput limits for large datasets or high-frequency replay.
- Whether smart symbology and point-in-time instrument definitions are available in the free tier.
Package facts
| License | Apache-2.0 permissive |
| Python support | Supports the current Python release >=3.10 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 8 packagesaiohttpdatabento-dbnnumpypandaspip-system-certspyarrowrequestszstandard |
| Maintenance | Actively maintained 9 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 1,745,295 / month, #3,597 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 4 - BetaOperating System :: OS IndependentProgramming Language :: Python :: 3Programming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.14Topic :: Office/Business :: FinancialTopic :: Office/Business :: Financial :: InvestmentTopic :: Software Development :: LibrariesTopic :: Software Development :: Libraries :: Python Modules |
Evidence: databento-0.83.0-py3-none-any.whl
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