duckdb-sqlalchemy is a DuckDB SQLAlchemy dialect for DuckDB and MotherDuck. It supports SQLAlchemy Core and ORM APIs for local DuckDB and MotherDuck connections.
The dialect handles pooling defaults, bulk inserts, type mappings, and cloud-specific configuration.
- SQLAlchemy compatibility: Core, ORM, Alembic, and reflection.
- MotherDuck support: Token handling, attach modes, session hints, and read scaling helpers.
- Operational defaults: Pooling defaults, transient retry for reads, and bulk insert optimization via Arrow/DataFrame registration.
- Maintained: Tracks current DuckDB releases with a long-term support posture.
| Component | Supported versions |
|---|---|
| Python | 3.9+ |
| SQLAlchemy | 1.3.22+ (2.x recommended) |
| DuckDB | 1.3.0+ (1.4.3 recommended) |
pip install duckdb-sqlalchemyfrom sqlalchemy import Column, Integer, String, create_engine
from sqlalchemy.orm import declarative_base, Session
Base = declarative_base()
class User(Base):
__tablename__ = "users"
id = Column(Integer, primary_key=True)
name = Column(String)
engine = create_engine("duckdb:///:memory:")
Base.metadata.create_all(engine)
with Session(engine) as session:
session.add(User(name="Ada"))
session.commit()
assert session.query(User).one().name == "Ada"export MOTHERDUCK_TOKEN="..."from sqlalchemy import create_engine
engine = create_engine("duckdb:///md:my_db")MotherDuck uses the md: database prefix. Tokens are picked up from MOTHERDUCK_TOKEN (or motherduck_token) automatically. If your token has special characters, URL-escape it or pass it via connect_args.
DuckDB URLs follow the standard SQLAlchemy shape:
duckdb:///<database>?<config>
Examples:
duckdb:///:memory:
duckdb:///analytics.db
duckdb:////absolute/path/to/analytics.db
duckdb:///md:my_db?attach_mode=single&access_mode=read_only&session_hint=team-a
Use the URL helpers to build connection strings safely:
from duckdb_sqlalchemy import URL, MotherDuckURL
local_url = URL(database=":memory:", memory_limit="1GB")
md_url = MotherDuckURL(database="md:my_db", attach_mode="single")This dialect defaults to NullPool for file/MotherDuck connections and SingletonThreadPool for :memory:. You can override pooling explicitly. For long-lived MotherDuck pools, use the performance helper or configure QueuePool, pool_pre_ping, and pool_recycle.
See docs/configuration.md and docs/motherduck.md for detailed guidance.
docs/index.md- GitHub Pages entrypointdocs/README.md- Docs indexdocs/overview.md- Overview and quick startdocs/getting-started.md- Minimal install + setup walkthroughdocs/migration-from-duckdb-engine.md- Migration guide from older dialectsdocs/connection-urls.md- URL formats and helpersdocs/motherduck.md- MotherDuck setup and optionsdocs/configuration.md- Connection configuration, extensions, filesystemsdocs/olap.md- Parquet/CSV scans and ATTACH workflowsdocs/pandas-jupyter.md- DataFrame registration and notebook usagedocs/types-and-caveats.md- Type support and known caveatsdocs/alembic.md- Alembic integration
Docs site (GitHub Pages):
https://leonardovida.github.io/duckdb-sqlalchemy/
examples/sqlalchemy_example.py- end-to-end exampleexamples/motherduck_read_scaling_per_user.py- per-user read scaling patternexamples/motherduck_queuepool_high_concurrency.py- QueuePool tuningexamples/motherduck_multi_instance_pool.py- multi-instance pool rotationexamples/motherduck_arrow_reads.py- Arrow results + streamingexamples/motherduck_attach_modes.py- workspace vs single attach mode
- Long-term maintenance: intended to remain supported.
- Compatibility: track current DuckDB and SQLAlchemy releases while preserving SQLAlchemy semantics.
- Breaking changes: only in major/minor releases with explicit notes in
CHANGELOG.md. - Security: open an issue with details; fixes are prioritized.
CHANGELOG.md- release notesROADMAP.md- upcoming work and priorities
See AGENTS.md for repo-specific workflow, tooling, and PR expectations. We welcome issues, bug reports, and high-quality pull requests.
MIT. See LICENSE.txt.