---
id: dbt-postgres
version: "1.11.0"
license: unclear
license_treatment: permissive
maintenance: active
---

# dbt-postgres — The set of adapter protocols and base functionality that supports integration with dbt-core

License: permissive · Maintenance: active · Downloads: 7.1M/mo

## What it is and what it does

dbt-postgres is the PostgreSQL adapter for dbt, the transformation tool that brings software engineering practices to data analytics. It enables you to write, test, and version-control SQL transformations as code, turning raw warehouse data into analysis-ready tables through dbt's templating, testing, and documentation framework.

The package bundles dbt-core with PostgreSQL-specific connection handling, dependency resolution, and query execution. It ships with psycopg2-binary by default for frictionless local development, though the documentation recommends compiling psycopg2 from source in production for performance gains. The adapter supports Python 3.10 through 3.14 and is actively maintained.

Use it for:

- Build modular, testable SQL transformation pipelines in PostgreSQL without writing boilerplate connection code
- Version-control and document data warehouse schemas as code alongside your analytics logic
- Implement data quality tests and lineage tracking for tables transformed from raw warehouse data
- Organize complex multi-step transformations (denormalization, filtering, aggregation) as a DAG of interdependent models
- Migrate transformation logic between environments (dev, staging, production) using dbt profiles

## Worth the install?

AI-flagged interpretation of the facts above — verify before relying.

dbt-postgres is a dbt adapter that connects dbt to PostgreSQL databases, enabling data transformation workflows using SQL and dbt's templating and testing framework.

Yes. dbt-postgres is actively maintained, has no known vulnerabilities, installs with low friction, and is the standard way to use dbt with PostgreSQL. Install it if you are building or maintaining data transformation pipelines in Postgres and want version control, testing, and documentation for your SQL logic. Consider compiling psycopg2 from source in production for better performance.

## Install

pip install dbt-postgres
uv add dbt-postgres
poetry add dbt-postgres

## Installing dbt-postgres

Before you install: Low install friction with a pure-Python wheel. Actively maintained with a release 29 days ago. Depends on dbt-core, dbt-adapters, dbt-common, agate, and psycopg2-binary; the description notes that psycopg2-binary is convenient for development but recommends building psycopg2 from source for production performance.

License in practice: Licensed under Apache Software License (permissive), allowing commercial use, modification, and distribution with minimal restrictions.

Quickstart:

pip install dbt-postgres

import dbt.adapters.postgres

# Configure dbt_project.yml with postgres profile, then run:
# dbt run

Requires Python 3.10 or later. PostgreSQL connection credentials must be configured in dbt profiles.yml before running transformations.

Verify before relying:

- Whether psycopg2-binary's pre-built wheel is sufficient for typical development workflows or if source compilation is routinely needed
- Performance characteristics and typical latency for transformation jobs on various data volumes

## Package facts

- License: not declared (permissive)
- Python support: supports_current
- Install friction: low
- Maintenance: active
- Downloads: 7.1M/month (top 5,000 on PyPI)
- Known vulnerabilities: none known

## Tags

dbt postgres adapter, transform data in postgres, dbt database integration, elt tool postgres, data warehouse transformation, sql transformation framework, postgres dbt connector, data-transformation, elt-tool, postgres-adapter

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