Overview Quickstart dbt Compatibility The Style Guide profiles.yml sources.yml Configuration Supported Databases

CLICKHOUSE

Column-oriented OLAP database for real-time analytics. Designed for sub-second queries over billions of rows.

DVT SUPPORT

✓ FEDERATION SOURCE

read in federation models

✓ FEDERATION TARGET

materialize federation results

✓ DEFAULT TARGET

run full dbt projects against it

✓ SEED TARGET

dvt seed --target loads here

DVT supports ClickHousebecause both dbt and Sling do: dbt drives standard materializations when it's your default target, Sling moves data in and out during federation. Connectivity for both layers is checked with dvt debug --all.

PREREQUISITES

Driver: clickhouse-connect — installed automatically by:

dvt sync

CONFIGURATION FIELDS

FIELD	TYPE	REQUIRED	DEFAULT	DESCRIPTION
type	string	yes	—	Must be `clickhouse`
host	string	yes	localhost	ClickHouse server hostname
port	integer	no	9000	Native protocol port
user	string	no	default	Database username
password	string	no	—	Database password
database	string	no	default	Database name
threads	integer	no	4	Number of parallel threads

PROFILES.YML EXAMPLE

my_project:
  target: ch_dev
  outputs:
    ch_dev:
      type: clickhouse
      host: localhost
      port: 9000
      user: default
      password: "{{ env_var('CH_PASSWORD') }}"
      database: analytics

SOURCES.YML EXAMPLE

sources:
  - name: clickhouse_data
    meta:
      connection: ch_dev
    database: analytics
    tables:
      - name: events
      - name: metrics

DBT ADAPTER FEATURES

When ClickHouse is your default target, every standard dbt model runs through the official dbt adapter — all of its documented capabilities apply unchanged:

MATERIALIZATIONS

INCREMENTAL STRATEGIES

NOTABLE CONFIGS

▸MergeTree engines
▸order_by
▸partition_by
▸TTL
▸needs BOTH transports: HTTP (clickhouse-connect) + native (clickhouse-driver) — dvt sync installs both

Official dbt ClickHouse adapter docs ↗

FEDERATION INCREMENTAL STRATEGIES

Strategies available when this engine is the target of a f_incremental model:

✓ Append✓ Delete+Insert✓ Merge