01
Reuse your dbt models
Kimo reads your marts as-is. Certify metrics on top of them instead of rebuilding logic.
fct_ · dim_ tables
Warehouses
ClickHouse + Kimo
Real-time OLAP, billions of rows. Query your warehouse live. Kimo pushes the SQL down, so nothing gets copied and nothing goes stale.
- Auth
- Read-only credentials
- Sync
- Live query
- Setup
- ≈ 10 min
Live demo workspace with fictional data · no signup, no credentials needed
kimo / connectors / clickhouseSyncing
Sync loglive query
- Succeeded:fct_orders+562 rowsnow
- Succeeded:fct_sessions+2,181 rows2m ago
- Succeeded:dim_customers+2,124 rows4m ago
- Succeeded:fct_orders+1,343 rows6m ago
Rows synced · 30 days
143M
Workspaces
18%
What you can do
What teams build with ClickHouse
ClickHouse on its own answers half the question. Joined with the rest of your stack in Kimo, it answers the other half.
02
Live queries, cached smartly
Push-down SQL with result caching keeps dashboards fast and warehouse spend predictable.
Cache hit 92%
03
Self-serve for business teams
Anyone can explore certified measures without writing SQL or waiting on the data team.
Certified metrics
Objects & tables
Exactly what gets synced
Kimo maps ClickHouse into clean, typed tables with primary keys and incremental cursors, so syncs stay fast and joins just work.
3 tables · 12 fields
Tables
fct_orders
Live query≈ 71,400,000 rows| Field | Type | Notes |
|---|---|---|
| order_id | id | Primary key |
| customer_id | id | References customer |
| revenue | decimal | Measure |
| ordered_at | timestamp | Incremental cursor |
Custom fields and extra objects are discovered automatically on each sync. Row counts are illustrative.
Sample model
From raw ClickHouse tables to a certified metric
A starter model Kimo suggests the moment ClickHouse is connected. Every join is editable.
ClickHouse · Revenue by segment
Orders fact table joined with the customer dimension and CRM accounts.
- ClickHousefct_orders
- HubSpotcompanies
- Google Sheetstargets
Model
customer_id
Measuresrevenueorders
Revenue · last 30 days
$58.9K+3.1% wk/wk
Fictional data · hover the chart for daily values
Setup
Connect ClickHouse in 10 min
No engineers, no pipelines to maintain. Kimo asks for the minimum access it needs and tells you exactly what it will read.
- 1
Create a dedicated role
Grant SELECT on the schemas Kimo should see, and a small warehouse for its queries.
- 2
Open network access
Allow Kimo’s static egress IPs, use an SSH tunnel, or run the on-prem agent inside your network.
- 3
Enter connection details
Credentials are encrypted at rest with a per-workspace key and tested before saving.
- 4
Pick schemas
Kimo reads the information schema and suggests models from your marts.
Create a read-only user
CREATE USER kimo_reader IDENTIFIED BY '<generated>'
SETTINGS readonly = 1;
GRANT SELECT ON events.* TO kimo_reader;Read-only, encrypted, revocable. Credentials are encrypted with a per-workspace key, never logged, and can be rotated without breaking your models.
Connect ClickHouse
Step 2 of 3 · Kimo demo workspace
- Reaching host
- Authenticating
- Reading schema
Read-only access
Illustration only · placeholder values, never real secrets
Works great with
Pair ClickHouse with the rest of your stack
Kimo suggests these joins automatically when both sources are connected.
FAQ
ClickHouse questions, answered
ClickHouse is queried live: Kimo compiles each chart to SQL and runs it on your warehouse, with a short result cache you control per dashboard.
ClickHouse · Read-only credentials · Live query
See your ClickHouse data in Kimo in 10 min.
Try it on the live demo workspace first, then connect your own account when you are ready.