Connect to adapters
Adapters are an essential component of dbt. At their most basic level, they are how dbt connects with the various supported data platforms. At a higher-level, adapters strive to give analytics engineers more transferrable skills as well as standardize how analytics projects are structured. Gone are the days where you have to learn a new language or flavor of SQL when you move to a new job that has a different data platform. That is the power of adapters in dbt — for more detail, refer to the Build, test, document, and promote adapters guide.
This section provides more details on different ways you can connect dbt to an adapter, and explains what a maintainer is.
Set up in dbt
Explore the fastest and most reliable way to deploy dbt by using the dbt platform, a hosted architecture that runs dbt across your organization. The dbt platform lets you seamlessly connect with a variety of trusted data platform providers directly in the dbt UI.
Install self-hosted dbt
Install self-hosted dbt locally using the command line. dbt communicates with a number of different data platforms by using a dedicated adapter plugin for each. When you install dbt locally, you'll also need to configure the specific adapter for your database, connect dbt v2 to dbt v1, and set up a profiles.yml file.
Trusted adapters ship with dbt v2 — when you install dbt, the supported data platforms are available out of the box, with no separate pip install per adapter needed.
Refer to adapter creation for more info.
Footnotes
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Use the PyPI package name when installing with
pip↩Adapter repo name PyPI package name dbt-layerdbt-layer-bigquery
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