How do I build my first data pipeline?
Start with one asset: a .sql or .py file with a YAML header that names it and declares dependencies. Add more assets, then run the whole graph with bruin run. No orchestrator to set up first. Bruin does this in one platform: ingestion, SQL and Python pipelines, quality checks, lineage, and an AI data analyst that answers in Slack, Microsoft Teams, and the browser.
Command
bruin runDefined in
SQL + YAML
Works with
Any Bruin-supported warehouse
What you get
How it works in code
/* @bruin
name: staging.orders
materialization:
type: table
@bruin */
SELECT id, amount, created_at FROM raw.ordersRun bruin run and Bruin runs your first pipeline end to end.
Related use cases
Build a SQL + Python pipeline on Snowflake
How do I run SQL and Python transformations together on Snowflake?
SQL and Python pipelinesMaterialize a table incrementally on Snowflake
How do I run incremental models on Snowflake without hand-writing merge logic?
SQL and Python pipelinesBuild a SQL + Python pipeline on BigQuery
How do I run SQL and Python transformations together on BigQuery?
SQL and Python, one pipeline
Open source. Define assets, declare dependencies, run the graph with bruin run.