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CloudQuery is an open-source ELT framework that empowers data engineers and developers to integrate, transform, and visualize data from any source to any destination. It's designed to handle a wide range of data integration and analysis tasks, making it a versatile tool for modern data stacks.

Key Features

  • Extensible through Plugins: Offers the flexibility to write custom plugins in multiple languages (Go, Python, Javascript, or Java), using the CloudQuery SDK powered by Apache Arrow.
  • High Performance: Optimized for speed, CloudQuery facilitates the quick synchronization of large datasets.
  • Open Source: Encourages contributions to its ecosystem, fostering innovation and collaboration among developers.
  • Versatile Data Integration: Enables extraction, transformation, and loading of data from cloud APIs into databases, data lakes, or streaming platforms.
  • Simple Configuration: Simplifies setup and synchronization tasks with a straightforward YAML configuration.


  • Unified Data Analysis: By facilitating integration with technologies like DuckDB, CloudQuery enables seamless data exploration and analysis.
  • Scalability: Its stateless plugin architecture can be scaled horizontally on any platform, meeting the growing data demands of organizations.
  • Elimination of Data Silos: Enhances collaboration between different organizational teams by unifying data.
  • Ease of Use: Its user-friendly nature, highlighted by an effortless setup process, makes it accessible for data engineers and developers at all skill levels.

For data engineers and developers looking to explore CloudQuery's capabilities, especially its integration with DuckDB and MotherDuck, diving into the official CloudQuery documentation and exploring the CloudQuery blog provide comprehensive guidance on deployment strategies, plugin development, and real-world applications.


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