dbt-snowflake
The Snowflake adapter plugin for dbt
Decision gist · record as of 2026-08-14
Yes. dbt-snowflake is a production-stable, actively maintained adapter with low install friction and no known vulnerabilities. Install it if you are using Snowflake and want to adopt dbt's SQL-based transformation and testing framework. It is the standard tool for this use case and carries minimal risk.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.10 or later; Snowflake account credentials and warehouse configuration must be set in profiles.yml before running dbt commands.
- Low install friction with a pure-Python wheel distribution.
- Actively maintained with a release 29 days old and recent commits; depends on dbt-core, dbt-adapters, dbt-common, snowflake-connector-python, and standard utilities (agate, certifi).
License · maintenance · safety
permissive license (permissive) — Licensed under Apache Software License (permissive), allowing commercial and private use with minimal restrictions.
last release 2026-07-16 (29 days) · last repo commit 2026-08-14 · 231 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 10,215,431 downloads/mo, #1,468 on PyPI
Alternatives
Verify before relying
pip install dbt-snowflake
In your dbt project's profiles.yml:
my_snowflake_db:
target: dev
outputs:
dev:
type: snowflake
account: [account_id]
user: [username]
password: [password]
database: [database_name]
schema: [schema_name]
warehouse: [warehouse_name]
Then run: dbt run- Whether the package includes built-in support for specific Snowflake features (e.g., dynamic tables, iceberg tables, or Snowflake-specific optimizations).
- Performance characteristics or scaling limits when working with very large datasets in Snowflake.
- Recommended thread pool sizing and concurrency tuning for different warehouse sizes.
What it is and what it does
dbt-snowflake is the official adapter that connects dbt to Snowflake, allowing data analysts and engineers to write SQL and YAML-based transformations that run directly in Snowflake. It bridges dbt's modeling and testing framework with Snowflake's cloud data warehouse, enabling version control, testing, documentation, and CI/CD workflows for data pipelines.
The package depends on dbt-core for the transformation engine, dbt-adapters and dbt-common for adapter infrastructure, snowflake-connector-python for Snowflake connectivity, and utility libraries (agate, certifi). It supports Python 3.10, 3.11, 3.12, and 3.13 on macOS, Windows, and Linux, and is classified as production-stable. With no known security vulnerabilities and active maintenance (latest release 2026-07-16), it is a mature choice for teams building analytics workflows on Snowflake.
Use it for
- Build and test SQL transformation models in Snowflake using dbt's YAML configuration and testing framework.
- Organize raw warehouse data into clean, documented analytics-ready tables with version control and lineage tracking.
- Implement CI/CD pipelines for data transformations, running tests and documentation generation on every commit.
- Denormalize and aggregate raw data into dimensional or fact tables for downstream BI tools and reporting.
- Collaborate on data modeling across teams using dbt's documentation, DAG visualization, and code review workflows.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes.
dbt-snowflake is a production-stable, actively maintained adapter with low install friction and no known vulnerabilities. Install it if you are using Snowflake and want to adopt dbt's SQL-based transformation and testing framework. It is the standard tool for this use case and carries minimal risk.
Install
dbt-snowflake on PyPI
Before you install
Low install friction with a pure-Python wheel distribution. Actively maintained with a release 29 days old and recent commits; depends on dbt-core, dbt-adapters, dbt-common, snowflake-connector-python, and standard utilities (agate, certifi).
Requires Python 3.10 or later; Snowflake account credentials and warehouse configuration must be set in profiles.yml before running dbt commands.
License in practice
Licensed under Apache Software License (permissive), allowing commercial and private use with minimal restrictions.
Quickstart
pip install dbt-snowflake
In your dbt project's profiles.yml:
my_snowflake_db:
target: dev
outputs:
dev:
type: snowflake
account: [account_id]
user: [username]
password: [password]
database: [database_name]
schema: [schema_name]
warehouse: [warehouse_name]
Then run: dbt runVerify before relying
- Whether the package includes built-in support for specific Snowflake features (e.g., dynamic tables, iceberg tables, or Snowflake-specific optimizations).
- Performance characteristics or scaling limits when working with very large datasets in Snowflake.
- Recommended thread pool sizing and concurrency tuning for different warehouse sizes.
Package facts
| License | permissive license permissive |
| Python support | Supports the current Python release >=3.10.0 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 6 packagesagatecertifidbt-adaptersdbt-commondbt-coresnowflake-connector-python |
| Maintenance | Actively maintained 29 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 10,215,431 / month, #1,468 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 5 - Production/StableLicense :: OSI Approved :: Apache Software LicenseOperating System :: MacOS :: MacOS XOperating System :: Microsoft :: WindowsOperating System :: POSIX :: LinuxProgramming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13 |
Evidence: dbt_snowflake-1.12.0-py3-none-any.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 › “dbt snowflake adapter”
- dbt-snowflakedbt-snowflake is the Snowflake adapter for dbt, enabling data…
- dbt-adaptersProvides base adapter protocols and shared functionality that…
- dbt-commonProvides shared utilities and common code used by dbt-core and dbt…
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 dbt-bigquery · streamsets · dbt-spark · dbt-postgres · dbt-fabricspark · dbt-glue · dbt-redshift · dbt-loom · dbt-dremio · dbt-oracle