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Warehouses

Snowflake + Kimo

Point Kimo at a Snowflake role and warehouse. Models compile to Snowflake SQL and run where your data lives.

Auth
Read-only credentials
Sync
Live query
Setup
≈ 10 min
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Live demo workspace with fictional data · no signup, no credentials needed

kimo / connectors / snowflakeSyncing
Sync loglive query
  • Succeeded:PROD.MARTS.DIM_PRODUCTS+124 rowsnow
  • Succeeded:PROD.MARTS.FCT_ORDERS+1,743 rows2m ago
  • Succeeded:PROD.MARTS.DIM_PRODUCTS+962 rows4m ago
  • Succeeded:PROD.MARTS.FCT_ORDERS+181 rows6m ago
Rows synced · 30 days
135.7M
Workspaces
10%
Simulated demo data
What you can do

What teams build with Snowflake

Snowflake on its own answers half the question. Joined with the rest of your stack in Kimo, it answers the other half.

01

Semantic layer on Snowflake

Certified measures compile to Snowflake SQL and run on your own warehouse.

Push-down SQL
02

Warehouse-aware scheduling

Refresh heavy dashboards on an XS warehouse overnight and serve cached results all day.

Credits ↓ 38%
03

Respect your RBAC

Kimo queries with a dedicated role, so row access policies and masking still apply.

Role-based
Objects & tables

Exactly what gets synced

Kimo maps Snowflake into clean, typed tables with primary keys and incremental cursors, so syncs stay fast and joins just work.

2 tables · 8 fields

PROD.MARTS.FCT_ORDERS

Live query≈ 842,000 rows
FieldTypeNotes
ORDER_IDstring
CUSTOMER_IDstring
NET_REVENUEstring
ORDERED_ATstring
Custom fields and extra objects are discovered automatically on each sync. Row counts are illustrative.
Sample model

From raw Snowflake tables to a certified metric

A starter model Kimo suggests the moment Snowflake is connected. Every join is editable.

Snowflake · Revenue by segment

Orders fact table joined with the customer dimension and CRM accounts.

Template
  • Snowflake
    PROD.MARTS.FCT_ORDERS
  • HubSpot
    companies
  • Google Sheets
    targets
Model
customer_id
Measuresrevenueorders
Revenue · last 30 days
$60.8K+3.9% wk/wk

Fictional data · hover the chart for daily values

Setup

Connect Snowflake 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. 1

    Create a dedicated role

    Grant SELECT on the schemas Kimo should see, and a small warehouse for its queries.

  2. 2

    Open network access

    Allow Kimo’s static egress IPs, use an SSH tunnel, or run the on-prem agent inside your network.

  3. 3

    Enter connection details

    Credentials are encrypted at rest with a per-workspace key and tested before saving.

  4. 4

    Pick schemas

    Kimo reads the information schema and suggests models from your marts.

Create a role and warehouse
CREATE ROLE KIMO_READER;
CREATE WAREHOUSE KIMO_XS WAREHOUSE_SIZE = XSMALL
  AUTO_SUSPEND = 60;
GRANT USAGE ON WAREHOUSE KIMO_XS TO ROLE KIMO_READER;
GRANT SELECT ON ALL TABLES IN DATABASE ANALYTICS
  TO ROLE 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 Snowflake
Step 2 of 3 · Kimo demo workspace
  • Reaching host
  • Authenticating
  • Reading schema
Read-only access
Illustration only · placeholder values, never real secrets
FAQ

Snowflake questions, answered

Snowflake is queried live: Kimo compiles each chart to SQL and runs it on your warehouse, with a short result cache you control per dashboard.

Snowflake · Read-only credentials · Live query

See your Snowflake data in Kimo in 10 min.

Try it on the live demo workspace first, then connect your own account when you are ready.

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