GeoAlchemy2
Using SQLAlchemy with Spatial Databases
Decision gist · record as of 2026-08-14
Yes. GeoAlchemy2 is actively maintained, has low install friction, carries a permissive MIT license, and fills a clear need for ORM-based spatial database access. It is well-established and supports current Python versions. Install it if you need to work with geographic data in a SQLAlchemy-based application.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires a spatial database backend (such as PostGIS) to be installed and configured separately; Python 3.10 or later.
- Low friction installation with only two runtime dependencies (SQLAlchemy and packaging).
- Active maintenance with recent releases and a stable repository.
License · maintenance · safety
MIT (permissive) — MIT license permits commercial and private use with minimal restrictions.
last release 2026-05-12 (94 days) · last repo commit 2026-07-22 · 709 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 5,163,891 downloads/mo, #2,152 on PyPI
Alternatives
Verify before relying
pip install geoalchemy2
from geoalchemy2 import Geometry
from sqlalchemy import Column, Integer, create_engine
from sqlalchemy.orm import declarative_base
Base = declarative_base()
class Location(Base):
__tablename__ = 'locations'
id = Column(Integer, primary_key=True)
geom = Column(Geometry('POINT'))- Which spatial database backends are supported (PostGIS, SpatiaLite, etc.)
- Whether a spatial database system must be installed separately
- Performance characteristics for large geographic datasets
What it is and what it does
GeoAlchemy2 is a Python toolkit that bridges SQLAlchemy and spatial databases, allowing you to work with geographic data types and spatial queries through an ORM interface. It builds on SQLAlchemy's declarative system to map geographic columns and operations to database-native spatial types, letting you query and manipulate geographic data using Python objects rather than raw SQL.
The package is designed for applications that need to store, retrieve, and analyze geographic information—such as location-based services, mapping applications, or GIS analysis workflows. It handles the translation between Python spatial objects and the spatial data types supported by your underlying database, abstracting away database-specific SQL syntax for common geographic operations.
Use it for
- Build location-based web services that query geographic points, polygons, or routes stored in a spatial database
- Develop GIS analysis tools that need to perform spatial operations like distance calculations or intersection tests through an ORM
- Create mapping applications that store and retrieve geographic features alongside relational data
- Implement geofencing or proximity-based filtering in applications backed by a spatial database
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes.
GeoAlchemy2 is actively maintained, has low install friction, carries a permissive MIT license, and fills a clear need for ORM-based spatial database access. It is well-established and supports current Python versions. Install it if you need to work with geographic data in a SQLAlchemy-based application.
Install
geoalchemy2 on PyPI
Before you install
Low friction installation with only two runtime dependencies (SQLAlchemy and packaging). Active maintenance with recent releases and a stable repository.
Requires a spatial database backend (such as PostGIS) to be installed and configured separately; Python 3.10 or later.
License in practice
MIT license permits commercial and private use with minimal restrictions.
Quickstart
pip install geoalchemy2
from geoalchemy2 import Geometry
from sqlalchemy import Column, Integer, create_engine
from sqlalchemy.orm import declarative_base
Base = declarative_base()
class Location(Base):
__tablename__ = 'locations'
id = Column(Integer, primary_key=True)
geom = Column(Geometry('POINT'))Verify before relying
- Which spatial database backends are supported (PostGIS, SpatiaLite, etc.)
- Whether a spatial database system must be installed separately
- Performance characteristics for large geographic datasets
Package facts
| License | MIT permissive |
| Python support | Supports the current Python release >=3.10 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 2 packagesSQLAlchemypackaging |
| Maintenance | Actively maintained 94 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 5,163,891 / month, #2,152 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 4 - BetaEnvironment :: PluginsIntended Audience :: Information TechnologyOperating System :: OS IndependentProgramming Language :: PythonProgramming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Topic :: Scientific/Engineering :: GIS |
Evidence: geoalchemy2-0.20.0-py3-none-any.whl
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