dbt-postgres
The set of adapter protocols and base functionality that supports integration with dbt-core
Decision gist · record as of 2026-08-14
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.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.10 or later.
- PostgreSQL connection credentials must be configured in dbt profiles.yml before running transformations.
- Low install friction with a pure-Python wheel.
License · maintenance · safety
permissive license (permissive) — Licensed under Apache Software License (permissive), allowing commercial use, modification, and distribution 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) · 7,080,609 downloads/mo, #1,790 on PyPI
Alternatives
Verify before relying
pip install dbt-postgres
import dbt.adapters.postgres
# Configure dbt_project.yml with postgres profile, then run:
# dbt run- 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
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 on this page. Verify before relying on it.
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
dbt-postgres on PyPI
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.
Requires Python 3.10 or later. PostgreSQL connection credentials must be configured in dbt profiles.yml before running transformations.
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 runVerify 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 | permissive license permissive |
| Python support | Supports the current Python release >=3.10.0 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 5 packagesagatedbt-adaptersdbt-commondbt-corepsycopg2-binary |
| Maintenance | Actively maintained 29 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 7,080,609 / month, #1,790 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 :: 3.13Programming Language :: Python :: 3.14 |
Evidence: dbt_postgres-1.11.0-py3-none-any.whl
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