---
id: dbt-clickhouse
version: "1.10.2"
license: Apache-2.0
license_treatment: permissive
maintenance: active
---

# dbt-clickhouse — The Clickhouse plugin for dbt (data build tool)

License: permissive · Maintenance: active · Downloads: 2.5M/mo

## What it is and what it does

dbt-clickhouse is a dbt adapter that brings dbt's data transformation and testing capabilities to ClickHouse databases. It translates dbt's model definitions, tests, and documentation workflows into ClickHouse-native SQL, enabling version-controlled, modular data pipelines on ClickHouse. The adapter supports standard dbt materializations (tables, views, incremental models) and adds ClickHouse-specific features like materialized views, distributed tables, and custom column codecs and TTL settings.

You install it alongside dbt-core and dbt-adapters, configure a ClickHouse connection in your dbt profiles, and then write dbt models in SQL or YAML. The adapter handles compilation, testing, documentation generation, and snapshots. It supports most dbt-utils macros and covers dbt-core features up to version 1.10, though Catalog integrations remain experimental.

Use it for:

- Build modular, version-controlled data pipelines in ClickHouse using dbt's model and macro framework.
- Run automated data quality tests and generate documentation for ClickHouse tables and transformations.
- Implement incremental and microbatch loading patterns to efficiently update large ClickHouse datasets.
- Configure ClickHouse-specific optimizations (indexes, projections, codecs, TTL) directly in dbt model definitions.
- Manage distributed table materializations and transformations across ClickHouse cluster nodes.
- Snapshot and track historical changes in ClickHouse tables using dbt's snapshot functionality.

## Worth the install?

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

A dbt adapter that enables data transformation and testing workflows on ClickHouse, supporting table, view, incremental, and materialized view materializations with ClickHouse-specific configurations.

Yes. The adapter is production-stable (Development Status 5), actively maintained with a release on 2026-08-13, has no known vulnerabilities, and supports current Python versions (3.10–3.13). Install it if you use ClickHouse and want to adopt dbt for data transformation. Be aware that dbt Cloud integration is not yet available, and Catalog integrations require workarounds.

## Install

pip install dbt-clickhouse
uv add dbt-clickhouse
poetry add dbt-clickhouse

## Installing dbt-clickhouse

Before you install: Low friction installation as a pure Python wheel. Actively maintained with a release within the last day and recent commits. Requires dbt-core and dbt-adapters as separate dependencies since v1.8, and two ClickHouse client libraries (clickhouse-connect and clickhouse-driver).

License in practice: Apache-2.0 permissive license allows commercial and private use with minimal restrictions, suitable for most production environments.

Quickstart:

pip install dbt-core dbt-clickhouse

from dbt.adapters.clickhouse import ClickhouseAdapter
# Configure via dbt profiles.yml with ClickHouse connection details

Requires Python 3.10 or later; dbt-core and dbt-adapters must be installed separately (v1.8+); ClickHouse server must be accessible with valid credentials.

Verify before relying:

- Whether Catalog integrations (e.g., Iceberg) workarounds are production-ready or experimental
- Performance characteristics on large-scale incremental and distributed materializations
- Compatibility with dbt Cloud (documentation states not yet available)

## Package facts

- License: Apache-2.0 (permissive)
- Python support: supports_current
- Install friction: low
- Maintenance: active
- Downloads: 2.5M/month (top 5,000 on PyPI)
- Known vulnerabilities: none known

## Tags

dbt adapter for clickhouse, clickhouse data transformation, dbt materialization clickhouse, data build tool clickhouse plugin, clickhouse incremental models, dbt testing on clickhouse, clickhouse dbt integration, dbt-adapter, data-transformation, analytics-engineering

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