sqlalchemy-redshift
Amazon Redshift Dialect for sqlalchemy
Decision gist · record as of 2026-08-14
Yes, if you are building a Python application against Amazon Redshift and want to use SQLAlchemy. The dialect is actively maintained, supports current Python versions (3.10–3.14), has no known vulnerabilities, and installs with low friction. You must separately choose and install a driver, but that is a one-time decision documented in the package's own guidance.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- You must install either psycopg2, redshift_connector, or a compatible PostgreSQL driver separately; the dialect does not provide it as a required dependency.
- Low friction installation; the package itself is a pure-Python wheel.
- However, you must separately install either psycopg2 or redshift_connector to establish connections—the dialect does not bundle these.
License · maintenance · safety
MIT (permissive) — MIT license is permissive; you may use, modify, and distribute this package with minimal restrictions, including in commercial software.
last release 2026-04-28 (108 days) · last repo commit 2026-04-28 · 228 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 5,411,556 downloads/mo, #2,106 on PyPI
Alternatives
Verify before relying
pip install sqlalchemy-redshift
import sqlalchemy as sa
engine = sa.create_engine('redshift+psycopg2://username@host.amazonaws.com:5439/database')- Whether redshift_connector is a drop-in alternative to psycopg2 for all use cases or has known limitations.
- Performance characteristics of table reflection and DDL compilation on large Redshift schemas.
- Compatibility with Redshift Spectrum and other advanced Redshift features beyond those mentioned in release notes.
What it is and what it does
sqlalchemy-redshift is a SQLAlchemy dialect that translates ORM queries and SQL expressions into Redshift-compatible SQL and handles connection management to Amazon Redshift clusters. It sits between your Python application and Redshift, allowing you to use SQLAlchemy's declarative ORM, query builder, and schema reflection tools without writing raw SQL.
The dialect implements Redshift-specific DDL compilation, datatype support (including GEOMETRY, SUPER, HLLSKETCH, and TIMETZ), and features like materialized views, spectrum table support, and IAM role-based COPY/UNLOAD commands. It requires a separate driver—either psycopg2 or redshift_connector—to establish actual database connections.
Use it for
- Build a data warehouse application using SQLAlchemy ORM models that map to Redshift tables without writing SQL.
- Reflect an existing Redshift schema into Python objects to enable programmatic table and column inspection.
- Execute parameterized queries and bulk operations (COPY, UNLOAD) against Redshift from a Python application.
- Migrate a PostgreSQL application to Redshift by swapping the connection string and dialect while reusing most ORM code.
- Generate Redshift DDL (CREATE TABLE, ALTER TABLE) from SQLAlchemy schema definitions in Alembic migrations.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you are building a Python application against Amazon Redshift and want to use SQLAlchemy.
The dialect is actively maintained, supports current Python versions (3.10–3.14), has no known vulnerabilities, and installs with low friction. You must separately choose and install a driver, but that is a one-time decision documented in the package's own guidance.
Install
sqlalchemy-redshift on PyPI
Before you install
Low friction installation; the package itself is a pure-Python wheel. However, you must separately install either psycopg2 or redshift_connector to establish connections—the dialect does not bundle these. Maintenance is active with a recent release and ongoing support for current Python versions (3.10–3.14).
You must install either psycopg2, redshift_connector, or a compatible PostgreSQL driver separately; the dialect does not provide it as a required dependency.
License in practice
MIT license is permissive; you may use, modify, and distribute this package with minimal restrictions, including in commercial software.
Quickstart
pip install sqlalchemy-redshift
import sqlalchemy as sa
engine = sa.create_engine('redshift+psycopg2://username@host.amazonaws.com:5439/database')Verify before relying
- Whether redshift_connector is a drop-in alternative to psycopg2 for all use cases or has known limitations.
- Performance characteristics of table reflection and DDL compilation on large Redshift schemas.
- Compatibility with Redshift Spectrum and other advanced Redshift features beyond those mentioned in release notes.
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 108 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 5,411,556 / month, #2,106 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 :: ConsoleIntended Audience :: DevelopersLicense :: OSI Approved :: MIT LicenseOperating System :: OS IndependentProgramming Language :: PythonProgramming Language :: Python :: 3Programming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.14 |
Evidence: sqlalchemy_redshift-1.0.0-py3-none-any.whl
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See also chalk-sqlalchemy-redshift · redshift-connector · sqlalchemy-risingwave · sqlalchemy-rdsiam · sqlalchemy-pgspider · sqlalchemy-cockroachdb · teradatasqlalchemy · sqlalchemy-jdbcapi · sqlalchemy_exasol · sqlalchemy-databricks