--- title: "aim vs sacred" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/aimhubio-aim-vs-idsia-sacred" tools: ["aimhubio-aim", "idsia-sacred"] --- # aim vs sacred *GraphCanon updated Aug 3, 2026* ## Verdict Pick aim if aim is an easy-to-use experiment tracker for Python ML projects with robust features like metadata tracking and compatibility with various frameworks; pick sacred if sacred is an experiment management tool for machine learning that emphasizes configuration management, logging, and reproducibility. [aim](https://aimstack.io) reports 6.2k GitHub stars, 401 forks, and 465 open issues, last pushed Jul 27, 2026. [sacred](https://github.com/IDSIA/sacred) has 4.4k stars, 393 forks, and 107 open issues, last pushed Oct 22, 2025. Figures are from public GitHub metadata via [aim's repository](https://github.com/aimhubio/aim) and [sacred's repository](https://github.com/IDSIA/sacred). | | [aim](/tools/aimhubio-aim.md) | [sacred](/tools/idsia-sacred.md) | | --- | --- | --- | | Tagline | An easy-to-use & supercharged open-source experiment tracker | A tool for experiment configuration, logging, and reproducibility | | Stars | 6,210 | 4,372 | | Forks | 401 | 393 | | Open issues | 465 | 107 | | Language | Python | Python | | Adopt for | Aim is an easy-to-use experiment tracker for Python ML projects with robust features like metadata tracking and compatibility with various frameworks. | Sacred is an experiment management tool for machine learning that emphasizes configuration management, logging, and reproducibility. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | Sacred is open-source under the MIT license, providing broad permissiveness in its use and modification across various applications. | | Categories | Evaluation & Observability, Model Training | Developer Tools, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [aim](/tools/aimhubio-aim.md) | [sacred](/tools/idsia-sacred.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Slowing (36%) | | Days since push | 0d | 284d | | Open issues (now) | 465 | 107 | | Full report | [trust report](/tools/aimhubio-aim/trust.md) | [trust report](/tools/idsia-sacred/trust.md) | ## Decision facts: aim - **Adopt for:** Aim is an easy-to-use experiment tracker for Python ML projects with robust features like metadata tracking and compatibility with various frameworks. ## Decision facts: sacred - **Pricing:** freemium - Being an open-source tool under the MIT license, Sacred can be used freely without any cost. - **Adopt for:** Sacred is an experiment management tool for machine learning that emphasizes configuration management, logging, and reproducibility. - **License detail:** Sacred is open-source under the MIT license, providing broad permissiveness in its use and modification across various applications. ## Choose when ### Choose aim if… - License: aim is Apache-2.0, sacred is MIT. - Tags unique to aim: ai, data-science, experiment tracking, mlflow. - Also covers Evaluation & Observability. - You are working on Python-based machine learning projects and need detailed experiment tracking to manage metadata effectively. ### Choose sacred if… - License: sacred is MIT, aim is Apache-2.0. - Pricing: Being an open-source tool under the MIT license, Sacred can be used freely without any cost.. - Tags unique to sacred: config injection, experiment management, logging, reproducibility. - Also covers Developer Tools. - When precise control over experiment configurations and their dependencies is required, allowing consistent reproduction of results. ## When NOT to use aim - You prefer comprehensive pre-built integrations with cloud services for MLOps processes that are not natively extensive in Aim. - Your project is primarily coded in languages other than Python; while language versatility might be desired, Aim specifically excels within the Python ecosystem. ## When NOT to use sacred - If your project does not require deep integration with MongoDB for logging purposes, as Sacred assumes this setup out-of-the-box without offering as much flexibility to other storage options. - When you need a tool with lightweight overhead, since Sacred's comprehensive feature set introduces more complexity suitable only for larger-scale projects. ## Common questions ### What is the difference between aim and sacred? aim: An easy-to-use & supercharged open-source experiment tracker. sacred: A tool for experiment configuration, logging, and reproducibility. See the comparison table for live GitHub stats and shared categories. ### When should I choose aim over sacred? Choose aim over sacred when License: aim is Apache-2.0, sacred is MIT; Tags unique to aim: ai, data-science, experiment tracking, mlflow; Also covers Evaluation & Observability; You are working on Python-based machine learning projects and need detailed experiment tracking to manage metadata effectively. ### When should I choose sacred over aim? Choose sacred over aim when License: sacred is MIT, aim is Apache-2.0; Pricing: Being an open-source tool under the MIT license, Sacred can be used freely without any cost.; Tags unique to sacred: config injection, experiment management, logging, reproducibility; Also covers Developer Tools; When precise control over experiment configurations and their dependencies is required, allowing consistent reproduction of results. ### When should I avoid aim? You prefer comprehensive pre-built integrations with cloud services for MLOps processes that are not natively extensive in Aim. Your project is primarily coded in languages other than Python; while language versatility might be desired, Aim specifically excels within the Python ecosystem. ### When should I avoid sacred? If your project does not require deep integration with MongoDB for logging purposes, as Sacred assumes this setup out-of-the-box without offering as much flexibility to other storage options. When you need a tool with lightweight overhead, since Sacred's comprehensive feature set introduces more complexity suitable only for larger-scale projects. ### Is aim or sacred more popular on GitHub? aim has more GitHub stars (6,210 vs 4,372). Stars measure visibility, not whether either tool fits your constraints. ### Are aim and sacred open source? Yes - both are open-source projects on GitHub (aim: Apache-2.0, sacred: MIT). ### Where can I find alternatives to aim or sacred? GraphCanon lists graph-backed alternatives at [aim alternatives](/tools/aimhubio-aim/alternatives) and [sacred alternatives](/tools/idsia-sacred/alternatives) ([aim markdown twin](/tools/aimhubio-aim/alternatives.md), [sacred markdown twin](/tools/idsia-sacred/alternatives.md)), ranked by typed relationship edges rather than popularity votes. ### Is there a machine-readable version of this comparison? Yes. The markdown twin at [this comparison](/compare/aimhubio-aim-vs-idsia-sacred.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, aim or sacred? aim: Very active. sacred: Slowing. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance. ### Where are the full trust reports for aim and sacred? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [aim trust report](/tools/aimhubio-aim/trust); [sacred trust report](/tools/idsia-sacred/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=aimhubio-aim`](/api/graphcanon/graph?tool=aimhubio-aim) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_