Ross ROSS = Recommend OSS · open-source software intelligence for agents

Bruin

Build data pipelines with SQL and Python, ingest data from different sources, add quality checks, and build end-to-end flows. observed · 2026-08-28

github.com/bruin-data/bruin · homepage · Go · Apache-2.0 (permissive) observed · 2026-08-28

Health v2 · maintenance only

91/100

  • Activity 99
  • Release rhythm 87
  • Longevity 80
How is this computed?

round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-03. Adoption (stars, forks) is never an input.

  • gap_med: 0
  • age_days: 1126
  • days_rel: 7
  • days_push: 7
  • n_releases_24m: 632

Full methodology

Adoption not part of the score

1678 stars · 87 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

Bruin is an end-to-end data platform whose CLI combines data ingestion (via its ingestr tool), SQL/Python/R transformations, and data quality checks into code-defined pipelines. ingestr itself is a command-line tool that copies data between databases and sources with a single command, supporting incremental loading strategies like append, merge, and delete+insert.

Use cases

  • copy data from postgres to snowflake with one command
  • ingest data from 70+ sources into a data warehouse without writing code
  • run sql and python transformations as a dependency-ordered pipeline
  • add data quality checks like unique and not_null to warehouse tables
  • schedule daily data pipelines with cron and get slack alerts on failure
  • incrementally load tables with merge or append strategies
  • visualize data lineage across pipeline assets
  • replace dbt, airbyte, and great expectations with one tool

When to choose

  • you want a single tool covering ingestion, transformation, and quality checks
  • you prefer pipelines defined in code (SQL/Python/YAML) in a git repository
  • you need simple no-code database-to-database data copying
  • you want built-in lineage, scheduling, and concurrency without a separate orchestrator

When to avoid

  • you need a full-featured distributed orchestrator like Airflow for complex workflows
  • you only want SQL transformations and already use dbt
  • you need streaming/real-time ingestion rather than batch loads
  • you require a permissive open-source license and the NOASSERTION license is a concern

Facets

cli-tool · maturity active

etl cli database workflow-automation scheduling data-science databases analytics developer-tools big-data cli cross-platform windows go python data-ingestion data-pipeline transformation data-quality dbt-alternative airbyte-alternative incremental-loading sql-pipelines lineage vscode-extension data-engineering macos linux

10 sources

Member repositories

RepositoryRoleHealth v2
bruin-data/bruinmain91
bruin-data/ingestrbackend88

For agents

markdown · JSON · MCP: product_card(name="bruin-data/bruin")

Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem