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Tags: ETL
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1–24 of 26 · Most stars

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.

dbt enables data analysts and engineers to transform their data using the same practices that software engineers use to build applications.

  • dbt-viewpoint
  • slack
  • pypa
  • data-modeling

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.

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

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

Neo4j Connector for Apache Spark, which provides bi-directional read/write access to Neo4j from Spark, using the Spark DataSource APIs

  • spark
  • neo4j-connector
  • cypher
  • neo4j-driver

Download, unpack from a ZIP/TAR/GZ/BZ2 archive, parse, correct, convert units and import Google Spreadsheets, XLS, ODS, XML, CSV, HTML, etc. into your ActiveRecord models. Uses RemoteTable gem internally.

A fast to develop, fast to run, Go based toolkit for ETL and feature extraction on Hadoop.

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

This is a library that provides generic functionalities for the implementation of imports. In addition to maximum performance and optimized memory consumption, Pacemaker can also be used to implement imports in distributed scenarios that place the highest demands on speed and stability.