Install dbt locally

Get dbt running on your machine in a few minutes. Choose your path:

Fusion + dbt extension (recommended)

Install the Fusion CLI Preview

The Fusion CLI delivers dbt Fusion engine performance benefits (faster parsing, compilation, and execution) but doesn't include LSP features. For the best dbt Fusion engine experience, install the dbt VS Code extension in VS Code or a compatible IDE.

Choose your preferred installation method:

 Pip installation for Windows, macOS, and Linux

python -m pip install --pre dbt

To upgrade to a newer version:

python -m pip install --upgrade --pre dbt

 CDN installation for macOS and Linux

curl -fsSL https://public.cdn.getdbt.com/fs/install/install.sh | sh -s -- --update

To use dbt immediately after installation, close and reopen your terminal or reload your shell so that the new $PATH is recognized:

exec $SHELL

To upgrade to a newer version:

dbt system update

 CDN installation for Windows

irm https://public.cdn.getdbt.com/fs/install/install.ps1 | iex

To use dbt immediately after installation, close and reopen or reload your shell so that the new Path is recognized:

Start-Process powershell

To upgrade to a newer version:

dbt system update

 Homebrew installation for macOS

brew install dbt

To upgrade to a newer version:

brew upgrade dbt

 Winget installation for Windows

winget install --id dbtLabs.dbt --exact

To upgrade to a specific version:

winget install --id dbtLabs.dbt --exact --version <version>

Run the following command to verify your installation:

dbt --version

You can use dbt or its Fusion alias dbtf (handy if you already have the Core or platform CLI installed). Default install path:

• macOS/Linux: $HOME/.local/bin/dbt
• Windows: C:\Users\<username>\.local\bin\dbt.exe

The installer adds this path automatically, but you may need to reload your shell for the dbtf command to work.

Install the extension

Install the dbt VS Code extension from the marketplace for VS Code and Cursor or Windsurf.

1. In your editor, open the Extensions tab and search for dbt.

2. Locate the extension from the publisher dbtLabsInc or dbt Labs Inc, then click Install.

   Search for the extension

3. Confirm that the extension is active by checking for the dbt Extension label in the status bar. Hover over the label to view diagnostic information.

   If you see the 'dbt Extension' label, the extension is activated

4. After the extension activates, it automatically downloads the correct dbt Language Server (LSP) for your operating system.

   The dbt Language Server will be installed automatically

Refer to the dbt VS Code extension docs for more information.

Troubleshooting

Common issues and resolutions:

• dbt command not found: Add the installation location to your $PATH.
• Version conflicts: Check that no other dbt Core or dbt CLI versions are installed or active on your machine.
• Installation permissions: Make sure your user account can install software locally.

Frequently asked questions

• Can I revert to my previous dbt installation?

  Yes. To test Fusion without affecting your existing workflows, use a separate environment or virtual machine.

More information about Fusion

Fusion marks a significant update to dbt. While many of the workflows you've grown accustomed to remain unchanged, there are a lot of new ideas, and a lot of old ones going away. The following is a list of the full scope of our current release of the Fusion engine, including implementation, installation, deprecations, and limitations:

• About the dbt Fusion engine
• About the dbt extension
• New concepts in Fusion
• Supported features matrix
• Installing Fusion CLI
• Installing VS Code extension
• Fusion release track
• Quickstart for Fusion
• Upgrade guide
• Fusion license agreement

dbt Core v2

Install dbt Core v2 CLI Alpha

dbt Core v2 is in alpha

dbt Core v2 is under active development and not recommended for production use. Features and APIs may change before the stable release. For stable local development, use Fusion.

dbt Core v2 is the next major version of dbt Core, built on the dbt Fusion engine runtime. Install it with pip, same as v1, but target the v2 prerelease package.

 Pip installation

python -m pip install --pre dbt-core

dbt --version

Confirm that the installed version begins with 2..

More information about Fusion

Fusion marks a significant update to dbt. While many of the workflows you've grown accustomed to remain unchanged, there are a lot of new ideas, and a lot of old ones going away. The following is a list of the full scope of our current release of the Fusion engine, including implementation, installation, deprecations, and limitations:

• About the dbt Fusion engine
• About the dbt extension
• New concepts in Fusion
• Supported features matrix
• Installing Fusion CLI
• Installing VS Code extension
• Fusion release track
• Quickstart for Fusion
• Upgrade guide
• Fusion license agreement

dbt Core v1

Install dbt Core v1 CLI

dbt Core v1 is the original open-source dbt engine. Install it with pip, Docker, or from source.

 Pip installation

Prerequisites

• Python (python --version or python3 --version)
• pip (pip --version or pip3 --version)

Does my operating system have prerequisites?

Your operating system may require pre-installation setup before installing dbt Core with pip. After downloading and installing any dependencies specific to your development environment, you can proceed with the pip installation of dbt Core.

CentOS

CentOS requires Python and some other dependencies to successfully install and run dbt Core.

To install Python and other dependencies:

sudo yum install redhat-rpm-config gcc libffi-devel \
  python-devel openssl-devel

MacOS

The MacOS requires Python 3.8 or higher to successfully install and run dbt Core.

To check the Python version:

python --version

If you need a compatible version, you can download and install Python version 3.9 or higher for MacOS.

If your machine runs on an Apple M1 architecture, we recommend that you install dbt via Rosetta. This is necessary for certain dependencies that are only supported on Intel processors.

Ubuntu/Debian

Ubuntu requires Python and other dependencies to successfully install and run dbt Core.

To install Python and other dependencies:

sudo apt-get install git libpq-dev python-dev python3-pip
sudo apt-get remove python-cffi
sudo pip install --upgrade cffi
pip install cryptography~=3.4

Windows

Windows requires Python and git to successfully install and run dbt Core.

Install Git for Windows and Python version 3.9 or higher for Windows.

For further questions, please see the Python compatibility FAQ

What version of Python can I use?

Use this table to match dbt Core versions with their compatible Python versions. New dbt minor versions will add support for new Python3 minor versions when all dependencies can support it. In addition, dbt minor versions will withdraw support for old Python3 minor versions before their end of life.

Python compatibility matrix

dbt-core version	v1.12	v1.11	v1.10	v1.9	v1.8	v1.7	v1.6	v1.5	v1.4	v1.3	v1.2	v1.1	v1.0
Python 3.14	✅	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
Python 3.13	✅	✅	⚠️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
Python 3.12	✅	✅	✅	✅	✅	✅	❌	❌	❌	❌	❌	❌	❌
Python 3.11	✅	✅	✅	✅	✅	✅	✅	✅	✅	❌	❌	❌	❌
Python 3.10	✅	✅	✅	✅	✅	✅	✅	✅	✅	✅	✅	✅	✅

Loading table...

⚠️ Python 3.13 is supported in dbt Core v1.10 for the Postgres adapter.

Adapter plugins and their dependencies are not always compatible with the latest version of Python.

Note that this shouldn't be confused with dbt Python models. If you're using a data platform that supports Snowpark, use the python_version config to run a Snowpark model with Python versions 3.9, 3.10, or 3.11.

Create a virtual environment

Unix/macOS

python3 -m venv .venv
source .venv/bin/activate

Windows

py -m venv .venv
.venv\Scripts\activate

To deactivate, run deactivate. To auto-activate in your new shell sessions, add an alias to your ~/.bashrc or ~/.zshrc:

alias env_dbt='source <PATH_TO_VIRTUAL_ENV_CONFIG>/bin/activate'

Install your adapter

Installing an adapter automatically installs dbt-core. Choose your adapter from Supported Data Platforms:

python -m pip install dbt-ADAPTER_NAME

To install dbt-core without an adapter (for tool integrations only):

python -m pip install dbt-core

Upgrade

# Upgrade adapter (and dbt-core)
python -m pip install --upgrade dbt-ADAPTER_NAME

# Downgrade to a specific version
python -m pip install --upgrade dbt-core==1.9

Install a prerelease

Use --pre to install prerelease versions. This may also install prerelease versions of other dependencies.

python3 -m pip install --pre dbt-ADAPTER_NAME

 Docker

dbt Core images are distributed via GitHub Packages and include pinned versions of dbt-core, one or more adapters, and all dependencies.

Prerequisites

• Docker installed
• Familiarity with adapters and Core versioning

Pull an image

Images follow the pattern ghcr.io/dbt-labs/<db_adapter_name>:<version_tag>. Available tags:

• latest — latest overall release
• <Major>.<Minor>.latest — latest patch for a version family (for example, 1.9.latest)

docker pull ghcr.io/dbt-labs/<db_adapter_name>:<version_tag>

Run dbt in a container

Bind-mount your project and profiles, then run any dbt command:

docker run \
--network=host \
--mount type=bind,source=/absolute/path/to/project,target=/usr/app \
--mount type=bind,source=/absolute/path/to/profiles.yml,target=/root/.dbt/profiles.yml \
<dbt_image_name> \
<dbt_command>

Note: bind-mount sources must be absolute paths. You may need to adjust --network settings depending on your warehouse host.

Build a custom image

If the pre-made images don't fit your use case, use the Dockerfile and README to build images with multiple adapters, third-party adapters, or different system architectures. Custom image builds are community-supported — open an issue or ask the community if you run into trouble.

 Source

Install from source to get unreleased code or a specific commit. Clone the repo and install with pip:

git clone https://github.com/dbt-labs/dbt-core.git
cd dbt-core
python -m pip install -r requirements.txt

For editable mode (changes take effect immediately):

python -m pip install -e editable-requirements.txt

Install an adapter from source

Install dbt-core first, then clone and install your adapter. For example, for Redshift:

git clone https://github.com/dbt-labs/dbt-redshift.git
cd dbt-redshift
python -m pip install .

For editable mode: python -m pip install -e .

For more details, read the contributing guidelines.

Pro tip: Using the --help flag

Most command-line tools, including dbt, support a --help flag that shows available commands and arguments. With dbt, you can use --help in two ways:

— dbt --help: Shows available dbt commands
— dbt run --help: Shows available flags for the run command

Next steps

• Configure environment variables to manage credentials.
• Configure your profiles.yml file.
• Configure your data platform connection.
• Create your first dbt project using the dbt init command.

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