ClickHouse/dbt-clickhouse
ClickHouse/dbt-clickhouse has 366 GitHub stars and 185 forks. GitHot measured +1 stars in 24 hours. Last checked 2026-11-12 12:58 UTC. Last push 2026-11-10.
The Clickhouse plugin for dbt (data build tool)
What you can do
- Table materialization
- View materialization
- Incremental materialization
- Microbatch incremental materialization
Measured star growth
- in 24h
- +1
- in 7 days
- Collecting history
- in 15 days
- Collecting history
- in 1 month
- Collecting history
Net star changes over overlapping periods, not daily totals. Missing measurements are left blank. Stars measure attention, not software quality.
README.md
Original
dbt-clickhouse
This plugin ports dbt functionality to Clickhouse.
The adapter works with both ClickHouse Cloud and self-hosted ClickHouse. You can start a free Cloud trial or install ClickHouse locally.
Documentation
See the ClickHouse website for the full documentation entry.
The documentation source is maintained in docs.
Installation
Use your favorite Python package manager to install the app from PyPI, e.g.
pip install dbt-core dbt-clickhouse
NOTE: Beginning in v1.8, dbt-core and adapters are decoupled. Therefore, the installation mentioned above explicitly includes both dbt-core and the desired adapter.If you use a version prior to 1.8.0 the pip installation command should look like this:
pip install dbt-clickhouse
Supported features
- Table materialization
- View materialization
- Incremental materialization
- Microbatch incremental materialization
- Materialized View materializations (uses the
TOform of MATERIALIZED VIEW, experimental) - Seeds
- Sources
- Docs generate
- Tests
- Snapshots
- Most dbt-utils macros (now included in dbt-core)
- Ephemeral materialization
- Distributed table materialization (experimental)
- Distributed incremental materialization (experimental)
- Contracts
- ClickHouse-specific column configurations (Codec, TTL...)
- ClickHouse-specific table settings (indexes, projections...)
Features up to dbt-core 1.12 are supported, including the --sample flag, and all deprecation warnings are fixed for future releases. Catalog integrations (e.g., Iceberg) introduced in dbt 1.10 are not yet natively supported in the adapter, but workarounds are available. See the Catalog Support section for details.
ClickHouse also works with dbt OSS and dbt v2 (Beta) and with the dbt platform (Private Beta). See the dbt OSS, dbt v2 and dbt platform documentation for availability and known limitations.
Contributing
We welcome contributions from the community to help improve the dbt-ClickHouse adapter. Whether you’re fixing a bug, adding a new feature, or enhancing documentation, your efforts are greatly appreciated!
Please take a moment to read our Contribution Guide to get started. The guide provides detailed instructions on setting up your environment, running tests, and submitting pull requests.
Original Author
ClickHouse wants to thank @silentsokolov for creating this connector and for their valuable contributions.
Explore related projects
Asabeneh/30-Days-Of-Python
The 30 Days of Python programming challenge is a step-by-step guide to learn the Python programming language in 30 days. This challenge may take more than 100 days. Follow your own pace. These videos may help too: https://www.youtube.com/channel/UC7PNRuno1rzYPb1xLa4yktw
78,560 starsgrafana/grafana
The open and composable observability and data visualization platform. Visualize metrics, logs, and traces from multiple sources like Prometheus, Loki, Elasticsearch, InfluxDB, Postgres and many more.
77,830 starsredis/redis
For developers, who are building real-time data-driven applications, Redis is the preferred, fastest, and most feature-rich cache, data structure server, and document and vector query engine.
77,395 starsapache/superset
Apache Superset is a Data Visualization and Data Exploration Platform
75,473 stars