Stop writing DAG boilerplate by hand — get a runnable orchestration pipeline from your SQL in seconds.
Paste SQL queries with dependency comments and get a runnable Airflow, Prefect or Dagster pipeline — task graph inferred, retries wired, schedule included.
Free tier: 3 DAG builds per month · or unlock forever for $4.99
DAG — 5 nodes · 4 edges
raw_orders
source
stg_orders
transform
stg_customers
transform
joined
transform
fct_revenue
sink
Mermaid
graph LR raw_orders([raw_orders]) --> stg_orders stg_orders --> joined stg_customers --> joined joined --> fct_revenue[(fct_revenue)]
Illustrative — graph is built from your SQL CTEs and table references.
Every card is something members actually do inside Datamata — not a vague promise.
Task graph, retries, schedule and connection stubs — the hour you spend every new pipeline, gone.
Comment your queries with what depends on what and the builder wires the task graph correctly.
Airflow DAG, Prefect flow or Dagster job — same SQL in, framework-native code out.
Supports Apache Airflow, Prefect and Dagster — pick your orchestrator
Feature deep-dives
See it work
Task graph, retries, schedule and connection stubs — the hour you spend every new pipeline, gone.
Try SQL to DAGDAG — 5 nodes · 4 edges
raw_orders
source
stg_orders
transform
stg_customers
transform
joined
transform
fct_revenue
sink
Mermaid
graph LR raw_orders([raw_orders]) --> stg_orders stg_orders --> joined stg_customers --> joined joined --> fct_revenue[(fct_revenue)]
Illustrative — graph is built from your SQL CTEs and table references.
Go deeper
Comment your queries with what depends on what and the builder wires the task graph correctly.
Browse all premium toolsIn practice
Airflow DAG, Prefect flow or Dagster job — same SQL in, framework-native code out.
Try SQL to DAGBuilt for Premium outcomes
Real decisions, not generic templates. Every workflow runs on live market data so your moves are backed by what employers are asking for now.
Supports Apache Airflow, Prefect and Dagster — pick your orchestrator
Infers task dependencies from query order and inline comments
Includes retry logic, schedule definition and connection reference stubs
Quick start guide
Paste your SQL queries in execution order with dependency comments — the builder handles the rest.
Add a short comment above each query describing its purpose and any upstream dependencies.
Tip: The clearer your dependency comments, the more accurate the task graph wiring.
Select Airflow, Prefect or Dagster and set a schedule interval or cron expression.
Check task IDs, connection references and the dependency graph before dropping it into your project.
Tip: Replace connection stub values with your actual Airflow connection IDs before running.
Use the dbt Model Generator first to produce the SQL, then the DAG Builder to orchestrate it — the two tools form a complete pipeline workflow.
What's included
Supports Apache Airflow, Prefect and Dagster — pick your orchestrator
Infers task dependencies from query order and inline comments
Includes retry logic, schedule definition and connection reference stubs
Free tier includes monthly builds to test the workflow
Start free, upgrade when you need more.
Pro
$9.99/moUnlimited builds across all orchestrators
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