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CloudQuery vs Jitsu

Learn how CloudQuery and Jitsu differ in their key features, development activity, technology stack and community adoption, so you can decide which of these etl & data integration tools is best for you.

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CloudQuery

CloudQuery is an open-source ELT platform that enables easy data integration from hundreds of cloud and security tools to any destination.
6,547stars+15(+0.2%)

Last 30 days

  • Last commit

    2 hours ago
  • Repository age

    6 years
  • Version

    v6.4.2
  • License

    MPL-2.0
  • Repository

    cloudquery
Screenshot of CloudQuery

Jitsu

Collect, transform, and sync data across your entire infrastructure with a flexible, code-based approach to data integration.
5,122stars+28(+0.5%)

Last 30 days

  • Last commit

    5 hours ago
  • Repository age

    6 years
  • Version

    1.11.0
  • License

    MIT
  • Self-hosted

    Yes
  • Repository

    jitsucom/jitsu
Screenshot of Jitsu

Detailed Comparison

Jitsu appears to have several advantages over CloudQuery, particularly in growth, licensing and features. Consider your specific needs regarding popularity, growth, activity, technology, maturity, licensing and features when making your decision.

Comparable
Community & Popularity

Both tools have similar popularity levels, with CloudQuery having 6,547 stars and Jitsu having 5,122 stars on GitHub. In terms of developer contributions, CloudQuery has 567 forks, indicating moderate developer engagement.

Jitsu wins
Growth Momentum

Jitsu is growing faster, adding 28 stars in the last 30 days (+0.5%) against adding 15 stars for CloudQuery (+0.2%). Jitsu is the smaller project of the two, so it is closing the gap rather than extending a lead.

Comparable
Development Activity

Both projects show recent activity, with CloudQuery last updated 2 hours ago and Jitsu 5 hours ago.

Comparable
Technology Stack

Both tools share common technology foundations, being built with JavaScript, Bash, Typescript. However, they differ in their additional technology choices: CloudQuery uses Python, Golang, Java while Jitsu leverages CSS, JSX, Next.js.

Comparable
Project Maturity

Both projects started around the same time, with CloudQuery beginning 6 years ago and Jitsu 6 years ago.

Jitsu wins
Licensing

Jitsu uses the MIT license, which is more permissive than CloudQuery's MPL-2.0 license, potentially offering greater flexibility for commercial use and integration.

Comparable
Use Cases & Features

Both tools serve similar use cases in ETL & Data Integration.

Jitsu wins
Hosting & Deployment

Jitsu provides self-hosting options for complete data control and customization, while CloudQuery may be primarily cloud-based or require different deployment approaches.