---
id: dbt-vertica
version: "1.8.6"
license: Apache License 2.0
license_treatment: permissive
maintenance: active
---

# dbt-vertica — Official vertica adapter plugin for dbt (data build tool)

License: permissive · Maintenance: active · Downloads: 799.9K/mo

## What it is and what it does

dbt-vertica is a dbt adapter that bridges dbt (a data transformation tool) and Vertica databases. It uses vertica-python to handle the connection layer, allowing you to write dbt models, tests, and documentation that execute as SQL transformations directly in Vertica. The adapter supports most core dbt features including table, view, and incremental materializations with multiple merge strategies, snapshots, seeds, tests, and unit testing.

You install it once alongside dbt-core, configure a profiles.yml file with your Vertica connection details (host, port, credentials, database, schema), and then use standard dbt commands (dbt run, dbt test, dbt build) to orchestrate your data pipeline. The adapter handles the translation of dbt's transformation logic into Vertica-native SQL, managing incremental updates, transaction control, and multi-threaded execution.

Use it for:

- Build incremental fact tables in Vertica using dbt's merge or delete+insert strategies to avoid full table rewrites.
- Run dbt tests and documentation generation on Vertica models as part of a data quality and governance workflow.
- Orchestrate multi-step SQL transformations in Vertica using dbt's DAG and dependency resolution.
- Execute dbt unit tests directly against Vertica to validate transformation logic before production deployment.
- Manage Vertica schema evolution and snapshots using dbt's snapshot feature for slowly-changing dimensions.

## Worth the install?

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

dbt adapter that enables data transformation workflows on Vertica databases, connecting dbt projects to Vertica via the vertica-python client.

Yes, if you use Vertica and dbt. The adapter is production-stable (Development Status 5), actively maintained, has no known vulnerabilities, and supports most dbt core features needed for typical data transformation workflows. Install friction is low. The only caveat is that external tables are untested and snapshot check_cols are not supported—verify these gaps don't block your use case.

## Install

pip install dbt-vertica
uv add dbt-vertica
poetry add dbt-vertica

## Installing dbt-vertica

Before you install: Low install friction; ships as a wheel with five runtime dependencies including dbt-core and vertica-python. Marked active maintenance with a release 38 days ago.

License in practice: Apache License 2.0 (permissive) — you can use, modify, and distribute this package freely in commercial and private projects, with minimal restrictions.

Quickstart:

pip install dbt-vertica

Then configure profiles.yml with:
  type: vertica
  host: [hostname]
  port: 5433
  username: [user]
  password: [pass]
  database: [db]
  schema: [schema]

Run: dbt run

Requires a running Vertica database instance (version 23.4.0-0 or compatible) and valid connection credentials in profiles.yml.

Verify before relying:

- Whether external tables are fully supported (fact sheet marks as 'Untested').
- Production readiness of snapshot check_cols feature (marked 'No' in support matrix).
- Compatibility with Vertica versions outside the tested range (23.4.0-0).

## Package facts

- License: Apache License 2.0 (permissive)
- Python support: supports_current
- Install friction: low
- Maintenance: active
- Downloads: 799.9K/month (top 15,000 on PyPI)
- Known vulnerabilities: none known

## Tags

dbt vertica adapter, vertica database transformation, dbt data warehouse adapter, vertica dbt plugin, dbt incremental models vertica, vertica dbt materialization, dbt vertica connection, dbt-adapter, data-transformation, vertica

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