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Tags: ETL
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1–19 of 19 · Most stars

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

  • batch-processing
  • kafka
  • pathway
  • python

SubQuery is an Open, Flexible, Fast and Universal data indexing framework for web3. Our mission is to help developers create the decentralised products of the future.

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.

Apache Camel is an open source integration framework with 350+ connectors. Write routes in Java, YAML, or XML. Run on Spring Boot, Quarkus, or standalone. Apache License 2.0.

A distributed data integration framework that simplifies common aspects of big data integration such as data ingestion, replication, organization and lifecycle management for both streaming and batch data ecosystems.

  • data
  • ingestion
  • replication
  • management

ETL framework for .NET (Parser / Writer for CSV, Flat, Xml, JSON, Key-Value, Parquet, Yaml, Avro formatted files)

:lipstick: Durable and asynchronous data imports for consuming data at scale and publishing testable SDKs.

  • porter
  • data-import
  • framework
  • data-transformation

An extensible Java framework for building event-driven applications that break up XML and non-XML data into chunks for data integration

  • java
  • smooks
  • enterprise-integration
  • etl

An Apache Spark framework for easy data processing, extraction as well as derivation for web archives and archival collections, developed at Internet Archive.

  • archivespark
  • spark-framework
  • spark
  • web-archiving

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.

  • dotnet
  • dotnet-core
  • etl
  • etl-framework