data-pipelines

Python ETL framework for stream processing, real-time analytics, LLM pipelines, and RAG.

Apache Airflow - A platform to programmatically author, schedule, and monitor workflows

An orchestration platform for the development, production, and observation of data assets.

Convert documents to structured data effortlessly. Unstructured is open-source ETL solution for transforming complex documents into clean, structured formats for language models. Visit our website to learn more about our enterprise grade Platform product for production grade workflows, partitioning, enrichments, chunking and embedding.

Apache DolphinScheduler is the modern data orchestration platform. Agile to create high performance workflow with low-code

Kedro is a toolbox for production-ready data science. It uses software engineering best practices to help you create data engineering and data science pipelines that are reproducible, maintainable, and modular.

🧙 Build, run, and manage data pipelines for integrating and transforming data.

🦀 event stream processing for developers to collect and transform data in motion to power responsive data intensive applications.

Preswald is a WASM packager for Python-based interactive data apps: bundle full complex data workflows, particularly visualizations, into single files, runnable completely in-browser, using Pyodide, DuckDB, Pandas, and Plotly, Matplotlib, etc. Build dashboards, reports, and notebooks that run offline, load fast, and share like a document.

Build data pipelines, the easy way 🛠️

A system for agentic LLM-powered data processing and ETL

Maestro: Netflix’s Workflow Orchestrator

Fast and efficient unstructured data extraction. Written in Rust with bindings for many languages.

MLeap: Deploy ML Pipelines to Production

AI agent tooling for data engineering workflows.

A lightweight workflow engine

Spark-Transformers: Library for exporting Apache Spark MLLIB models to use them in any Java application with no other dependencies.