--- title: "data-juicer vs mage-ai" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/datajuicer-data-juicer-vs-mage-ai-mage-ai" tools: ["datajuicer-data-juicer", "mage-ai-mage-ai"] --- # data-juicer vs mage-ai *GraphCanon updated Sep 20, 2026* ## Verdict Pick data-juicer if a Python library for foundational AI model data processing, offering a pipeline for tasks like instruction tuning and synthetic data generation; pick mage-ai if mage OSS offers a self-hosted Python-centric notebook-style UI for creating production-grade data pipelines with modular code blocks. [data-juicer](https://datajuicer.github.io/data-juicer/) reports 6.9k GitHub stars, 404 forks, and 59 open issues, last pushed Aug 13, 2026. [mage-ai](https://www.mage.ai) has 8.8k stars, 990 forks, and 624 open issues, last pushed Sep 11, 2026. Figures are from public GitHub metadata via [data-juicer's repository](https://github.com/datajuicer/data-juicer) and [mage-ai's repository](https://github.com/mage-ai/mage-ai). | | [data-juicer](/tools/datajuicer-data-juicer.md) | [mage-ai](/tools/mage-ai-mage-ai.md) | | --- | --- | --- | | Tagline | Data processing for and with foundation models | Build, run and manage data pipelines for integrating and transforming data | | Stars | 6,897 | 8,823 | | Forks | 404 | 990 | | Open issues | 59 | 624 | | Language | Python | Python | | Adopt for | A Python library for foundational AI model data processing, offering a pipeline for tasks like instruction tuning and synthetic data generation. | Mage OSS offers a self-hosted Python-centric notebook-style UI for creating production-grade data pipelines with modular code blocks. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | Apache-2.0 | | Categories | Data & Retrieval, Model Training | Data & Retrieval | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [data-juicer](/tools/datajuicer-data-juicer.md) | [mage-ai](/tools/mage-ai-mage-ai.md) | | --- | --- | --- | | Days since push | 4d | 6d | | Open issues (now) | 59 | 624 | | Stars delta | +166 (30d) | +33 (30d) | | Open issues delta | -3 (30d) | +5 (30d) | | Full report | [trust report](/tools/datajuicer-data-juicer/trust.md) | [trust report](/tools/mage-ai-mage-ai/trust.md) | ## Shared compatibility - **Python**: [data-juicer](/tools/datajuicer-data-juicer.md) - Python runtime; [mage-ai](/tools/mage-ai-mage-ai.md) - Python runtime ## Decision facts: data-juicer - **Adopt for:** A Python library for foundational AI model data processing, offering a pipeline for tasks like instruction tuning and synthetic data generation. ## Decision facts: mage-ai - **Adopt for:** Mage OSS offers a self-hosted Python-centric notebook-style UI for creating production-grade data pipelines with modular code blocks. ## Choose when ### Choose data-juicer if… - Tags unique to data-juicer: foundation-models, instruction-tuning, large-language-models, llm. - Also covers Model Training. - When you need to preprocess large datasets specifically for training large language models (LLMs) with pipelines that support sophisticated processes like instruction tuning. ### Choose mage-ai if… - Tags unique to mage-ai: artificial-intelligence, data-pipelines, machine-learning, python. - You need a local, self-hosted solution for building ETL tasks or orchestrating transformations. - More GitHub stars (8.8k vs 6.9k) - visibility, not fit. ## When NOT to use data-juicer - If your project does not involve foundational AI model training or if you do not require advanced data processing capabilities such as synthetic data generation. ## When NOT to use mage-ai - You need a cloud-hosted service with pre-provisioned storage and compute resources. - Looking for real-time collaboration features beyond the notebook-style interface. - Need support for non-Python, SQL, R languages in pipeline creation. ## Common questions ### What is the difference between data-juicer and mage-ai? data-juicer: Data processing for and with foundation models. mage-ai: Build, run and manage data pipelines for integrating and transforming data. See the comparison table for live GitHub stats and shared categories. ### When should I choose data-juicer over mage-ai? Choose data-juicer over mage-ai when Tags unique to data-juicer: foundation-models, instruction-tuning, large-language-models, llm; Also covers Model Training; When you need to preprocess large datasets specifically for training large language models (LLMs) with pipelines that support sophisticated processes like instruction tuning. ### When should I choose mage-ai over data-juicer? Choose mage-ai over data-juicer when Tags unique to mage-ai: artificial-intelligence, data-pipelines, machine-learning, python; You need a local, self-hosted solution for building ETL tasks or orchestrating transformations; More GitHub stars (8.8k vs 6.9k) - visibility, not fit. ### When should I avoid data-juicer? If your project does not involve foundational AI model training or if you do not require advanced data processing capabilities such as synthetic data generation. ### When should I avoid mage-ai? You need a cloud-hosted service with pre-provisioned storage and compute resources. Looking for real-time collaboration features beyond the notebook-style interface. Need support for non-Python, SQL, R languages in pipeline creation. ### Is data-juicer or mage-ai more popular on GitHub? mage-ai has more GitHub stars (8,823 vs 6,897). Stars measure visibility, not whether either tool fits your constraints. ### Are data-juicer and mage-ai open source? Yes - both are open-source projects on GitHub (data-juicer: Apache-2.0, mage-ai: Apache-2.0). ### Where can I find alternatives to data-juicer or mage-ai? GraphCanon lists graph-backed alternatives at [data-juicer alternatives](/tools/datajuicer-data-juicer/alternatives) and [mage-ai alternatives](/tools/mage-ai-mage-ai/alternatives) ([data-juicer markdown twin](/tools/datajuicer-data-juicer/alternatives.md), [mage-ai markdown twin](/tools/mage-ai-mage-ai/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/datajuicer-data-juicer-vs-mage-ai-mage-ai.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, data-juicer or mage-ai? data-juicer: Very active. mage-ai: Very active. 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 data-juicer and mage-ai? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [data-juicer trust report](/tools/datajuicer-data-juicer/trust); [mage-ai trust report](/tools/mage-ai-mage-ai/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=datajuicer-data-juicer`](/api/graphcanon/graph?tool=datajuicer-data-juicer) - 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/_