pymongoarrow
Tools for using NumPy, Pandas, Polars, and PyArrow with MongoDB
Decision gist · record as of 2026-08-14
Yes. PyMongoArrow is actively maintained, has no known vulnerabilities, and solves a specific problem—efficient materialization of MongoDB data into analytical formats. The permissive Apache license and broad platform support (Python 3.10–3.14 on macOS, Linux, Windows) make it a low-risk addition. Install it if you regularly need to move MongoDB query results into Arrow, Pandas, or NumPy for analysis.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires MongoDB server connection; pandas optional but needed for DataFrame output; not supported on big-endian systems.
- Medium install friction due to compiled wheels for multiple Python versions and platforms.
- Active maintenance with recent release (29 days ago) and ongoing repository activity.
License · maintenance · safety
Apache License, Version 2.0 (permissive) — Apache License 2.0 (permissive) allows commercial and private use with minimal restrictions; you may use, modify, and distribute this package freely.
last release 2026-07-16 (29 days) · last repo commit 2026-08-04 · 116 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 228,756 downloads/mo, #9,146 on PyPI
Alternatives
Verify before relying
pip install pymongoarrow
from pymongoarrow.monkey import patch_all
from pymongo import MongoClient
patch_all()
client = MongoClient()
data_frame = client.db.collection.find_pandas_all({})- Performance characteristics when materializing large result sets into memory
- Schema inference behavior when schema parameter is omitted
- Compatibility with MongoDB Atlas connection strings beyond the documented srv extra
What it is and what it does
PyMongoArrow is a companion library to PyMongo that bridges MongoDB query results into columnar in-memory formats. It extends PyMongo's collection API with methods like find_pandas_all(), find_arrow_all(), and find_numpy_all() to materialize query results directly as Arrow tables, Pandas DataFrames, or NumPy arrays without intermediate serialization steps.
The library is designed for analytical workloads where you need MongoDB data in typed, contiguous-in-memory arrays. It supports optional schema specification for type safety and can infer schemas automatically. Runtime dependencies include pyarrow, pymongo, numpy, and packaging; pandas is optional for DataFrame functionality.
Use it for
- Export MongoDB query results as Pandas DataFrames for data analysis and machine learning pipelines
- Load MongoDB collections into Apache Arrow tables for efficient columnar processing
- Convert MongoDB documents to NumPy arrays for numerical computing workflows
- Materialize large MongoDB result sets with explicit schema validation for type safety
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes.
PyMongoArrow is actively maintained, has no known vulnerabilities, and solves a specific problem—efficient materialization of MongoDB data into analytical formats. The permissive Apache license and broad platform support (Python 3.10–3.14 on macOS, Linux, Windows) make it a low-risk addition. Install it if you regularly need to move MongoDB query results into Arrow, Pandas, or NumPy for analysis.
Install
pymongoarrow on PyPI
Before you install
Medium install friction due to compiled wheels for multiple Python versions and platforms. Active maintenance with recent release (29 days ago) and ongoing repository activity.
Requires MongoDB server connection; pandas optional but needed for DataFrame output; not supported on big-endian systems.
License in practice
Apache License 2.0 (permissive) allows commercial and private use with minimal restrictions; you may use, modify, and distribute this package freely.
Quickstart
pip install pymongoarrow
from pymongoarrow.monkey import patch_all
from pymongo import MongoClient
patch_all()
client = MongoClient()
data_frame = client.db.collection.find_pandas_all({})Verify before relying
- Performance characteristics when materializing large result sets into memory
- Schema inference behavior when schema parameter is omitted
- Compatibility with MongoDB Atlas connection strings beyond the documented srv extra
Package facts
| License | Apache License, Version 2.0 permissive |
| Python support | Supports the current Python release >=3.10 |
| Install friction | Medium. Platform-specific wheel |
| Runtime dependencies | 4 packagespyarrowpymongonumpypackaging |
| Maintenance | Actively maintained 29 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 228,756 / month, #9,146 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 3 - AlphaIntended Audience :: DevelopersIntended Audience :: Science/ResearchLicense :: OSI Approved :: Apache Software LicenseOperating System :: MacOS :: MacOS XOperating System :: POSIXProgramming Language :: Python :: 3Programming Language :: Python :: 3 :: OnlyProgramming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.14Programming Language :: Python :: Implementation :: CPythonTopic :: Database |
Evidence: pymongoarrow-1.15.0-cp310-cp310-macosx_10_9_x86_64.whl; pymongoarrow-1.15.0-cp310-cp310-macosx_11_0_arm64.whl; pymongoarrow-1.15.0-cp310-cp310-manylinux_2_24_aarch64.manylinux_2_28_aarch64.whl; pymongoarrow-1.15.0-cp310-cp310-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl; pymongoarrow-1.15.0-cp310-cp310-win_amd64.whl; pymongoarrow-1.15.0-cp311-cp311-macosx_10_9_x86_64.whl; pymongoarrow-1.15.0-cp311-cp311-macosx_11_0_arm64.whl; pymongoarrow-1.15.0-cp311-cp311-manylinux_2_24_aarch64.manylinux_2_28_aarch64.whl; pymongoarrow-1.15.0-cp311-cp311-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl; pymongoarrow-1.15.0-cp311-cp311-win_amd64.whl; pymongoarrow-1.15.0-cp312-cp312-macosx_10_9_x86_64.whl; pymongoarrow-1.15.0-cp312-cp312-macosx_11_0_arm64.whl; pymongoarrow-1.15.0-cp312-cp312-manylinux_2_24_aarch64.manylinux_2_28_aarch64.whl; pymongoarrow-1.15.0-cp312-cp312-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl; pymongoarrow-1.15.0-cp312-cp312-win_amd64.whl; pymongoarrow-1.15.0-cp313-cp313-macosx_10_9_x86_64.whl; pymongoarrow-1.15.0-cp313-cp313-macosx_11_0_arm64.whl; pymongoarrow-1.15.0-cp313-cp313-manylinux_2_24_aarch64.manylinux_2_28_aarch64.whl; pymongoarrow-1.15.0-cp313-cp313-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl; pymongoarrow-1.15.0-cp313-cp313-win_amd64.whl
Tags
Let your AI agent find packages like this
Example. Real query, live index.
You found this page by searching. An agent finds it by wishing: SkillFed indexes 14,416 PyPI packages by what they can do, searchable in plain language.
wish › “mongodb to arrow conversion”
- pymongoarrowPyMongoArrow converts MongoDB query results into Apache Arrow tables,…
- geoarrow-pyarrowProvides Python bindings for the GeoArrow specification, enabling…
- arrow-odbcReads data from ODBC data sources directly into Apache Arrow record…
Give your agent the search over MCP, or paste the wish link into any chat.
More Database packages
psycopg2-binary is a PostgreSQL database adapter for Python that implements the DB API 2.0 specification, enabling Python applications to connect to and query PostgreSQL databases with thread-safe concurrent operations.
Python client library for connecting to and executing commands against Redis key-value stores, supporting both synchronous and asynchronous operations.
Install it if your application needs to interact with Redis; the only prerequisite is a running Redis server instance.
YDB Python SDK is the official client library for connecting to and querying YDB databases from Python applications.
Install it if you need to connect Python applications to YDB databases.
Connects Python applications to Snowflake data warehouses using the DB API 2.0 specification, enabling SQL queries, data transfers, and warehouse operations.
sqlparse tokenizes SQL text into a tree of statements, clauses, and expressions, and provides functions to split scripts, format queries, and inspect parsed tokens without validating dialect or syntax.
Install it if you need to manipulate, format, or analyze SQL text programmatically.
Provides base adapter protocols and shared functionality that database adapters use to integrate with dbt-core, handling connections, dialect translation, relation caching, and core interface management.
See also pymongo · Flask-PyMongo · pymongoexplain · pymongo_inmemory · mongoengine · bson · mongomock · feather-format · beanie · curatorbin