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Tag: Data pipelines and messaging
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1–24 of 36 · Most stars

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

  • batch-processing
  • kafka
  • pathway
  • python

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

Luigi is a Python module that helps you build complex pipelines of batch jobs. It handles dependency resolution, workflow management, visualization etc. It also comes with Hadoop support built in.

  • python
  • luigi
  • orchestration-framework
  • scheduling

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

  • workflow-schedule
  • azkaban
  • airflow
  • task-scheduler

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.

  • kedro
  • hacktoberfest
  • mlops
  • python

[SIGMOD'27] Easy Data Preparation with latest LLMs-based Operators and Pipelines.

  • data
  • data-cleaning
  • data-pipelines
  • data-processing

Data pipelines for cloud config and security data. Build cloud asset inventory, CSPM, FinOps, and vulnerability management solutions. Extract from AWS, Azure, GCP, and 70+ cloud and SaaS sources.

Meltano: the declarative code-first data integration engine that powers your wildest data and ML-powered product ideas. Say goodbye to writing, maintaining, and scaling your own API integrations.

  • dataops
  • dataops-platform
  • elt
  • open-source

Open-source low code data preparation library in python. Collect, clean and visualization your data in python with a few lines of code.

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