Durable DAG workflow engine in one Rust binary — an open-source, lightweight Airflow alternative.
Lightweight self-hosted workflow scheduler in a single Go binary — an open-source Airflow/Azkaban alternative. Embedded SQLite, DAGs (cron + dependencies + backfill), polyglot tasks (shell/Python/SQL/JAR/HTTP), web console, REST API, and a built-in MCP server for AI agents. Linux & macOS.
Rust-native data-pipeline orchestrator: event-sourced state, compile-time DAG validation, virtual environments, plan/apply deploys, and column-level SQL lineage — single binary, zero dependencies.
Self-hosted workflow engine that combines drag-drop DAGs with real code execution (Python/Node/Shell/Docker), 4 pluggable queue backends, and an AES-256 secret vault — in 140 MB of RAM. AGPL-3.0.
Faster, cheaper, more trustworthy data analysis for humans and AI agents. A Python library that turns data-science scripts into a cached, reproducible, lineage-tracked pipeline — reruns only what a parameter, data, or code change affects. No server, no account.
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