Python ETL framework for stream processing, real-time analytics, LLM pipelines, and RAG.
- batch-processing
- kafka
- pathway
- python
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Python ETL framework for stream processing, real-time analytics, LLM pipelines, and RAG.
Open-source data movement for ELT pipelines and AI agents — from APIs, databases & files to warehouses, lakes, and AI applications. Both self-hosted and Cloud.
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.
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.
A lightweight opinionated ETL framework, halfway between plain scripts and Apache Airflow
Build data pipelines with SQL and Python, ingest data from different sources, add quality checks, and build end-to-end flows.
Python Streaming DataFrames for Kafka
Open-source ETL/ELT you deploy on your own servers or cloud. Built on DuckDB: no-code/low-code visual pipelines or SQL, 385 components, dbt, CDC, data quality, reverse ETL, lineage, MCP for AI agents. No vendor cloud, no per-row billing.
visual data prep powered by python
An extensible Java framework for building event-driven applications that break up XML and non-XML data into chunks for data integration
EtlKit is a lightweight ETL (extract · transform · load) library and data integration toolbox for .NET. Build your own data pipelines programmatically in C# — readable, testable, and tracked in source control like the rest of your code.