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Two short guided tours: the Datattach workspace itself, and what a dbt project can look like with Datattach.
Schema explorer
▼
postgres
▼
crm
▶ customers
▶
snowflake
▶
mysql
▶
iceberg
Ctrl+Enter to run
Run
SELECT c.name, SUM(o.total)
FROM postgres.crm.customers c
JOIN snowflake.sales.orders o … View as: Admin row filter applied
Explore the platform
The Datattach workspace: a schema explorer full of different engines, a SQL editor, and the guardrails behind every table.
- Run a cross-source join — Postgres & Snowflake in one SELECT
- Flip between an admin and an analyst and watch the results change
- Open the access rules behind it — row filters and column masks
models/
├─ staging/
│ ├─ stg_customers.sql # postgres
│ ├─ stg_orders.sql # snowflake
│ └─ sources.yml # + ingestion
└─ marts/
└─ customer_lifetime_value.sql 3 engines 0 pipelines
The dbt workflow
A read-only dbt project pointed at one endpoint — folder structure and YAML doing work that usually takes a whole toolchain.
- A normal dbt project where one model joins two databases
- Ingestion declared in YAML — no separate EL tool in the stack
- Lineage and a dbt run that spans three engines
Both tours take about two minutes and are guided — or skip the guide and
just click around.
When you're done, book a demo.