--- title: "datatrove vs llama-hub" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/huggingface-datatrove-vs-run-llama-llama-hub" tools: ["huggingface-datatrove", "run-llama-llama-hub"] --- # datatrove vs llama-hub *GraphCanon updated Aug 8, 2026* ## Verdict Pick datatrove if datatrove is ideal for users needing platform-agnostic customizable pipeline blocks for data processing and transformation across various file formats with built-in support for distributed computing options; pick llama-hub if community-driven data loaders for LlamaIndex/LangChain. [datatrove](https://github.com/huggingface/datatrove) reports 3.3k GitHub stars, 288 forks, and 93 open issues, last pushed Aug 6, 2026. [llama-hub](https://llamahub.ai/) has 3.5k stars, 721 forks, and 96 open issues, last pushed Mar 1, 2024. Figures are from public GitHub metadata via [datatrove's repository](https://github.com/huggingface/datatrove) and [llama-hub's repository](https://github.com/run-llama/llama-hub). | | [datatrove](/tools/huggingface-datatrove.md) | [llama-hub](/tools/run-llama-llama-hub.md) | | --- | --- | --- | | Tagline | Platform-agnostic customizable pipeline processing blocks for data processing and transformation. | A library of data loaders for LLMs made by the community | | Stars | 3,250 | 3,469 | | Forks | 288 | 721 | | Open issues | 93 | 96 | | Language | Python | Jupyter Notebook | | Adopt for | Datatrove is ideal for users needing platform-agnostic customizable pipeline blocks for data processing and transformation across various file formats with built-in support for distributed computing options. | community-driven data loaders for LlamaIndex/LangChain | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | MIT | | Categories | Data & Retrieval, Inference & Serving, Model Training | Data & Retrieval, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [datatrove](/tools/huggingface-datatrove.md) | [llama-hub](/tools/run-llama-llama-hub.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Archived (8%) | | Days since push | 0d | 889d | | Archived on GitHub | No | Yes | | Open issues (now) | 93 | 96 | | Full report | [trust report](/tools/huggingface-datatrove/trust.md) | [trust report](/tools/run-llama-llama-hub/trust.md) | ## Shared compatibility - **Python**: [datatrove](/tools/huggingface-datatrove.md) - Python runtime; [llama-hub](/tools/run-llama-llama-hub.md) - Python runtime ## Decision facts: datatrove - **Adopt for:** Datatrove is ideal for users needing platform-agnostic customizable pipeline blocks for data processing and transformation across various file formats with built-in support for distributed computing options. ## Decision facts: llama-hub - **Adopt for:** community-driven data loaders for LlamaIndex/LangChain ## Choose when ### Choose datatrove if… - datatrove is primarily Python; llama-hub is Jupyter Notebook. - License: datatrove is Apache-2.0, llama-hub is MIT. - Tags unique to datatrove: data-processing, distributed-computing, file-formats-support, pipelines. - Also covers Inference & Serving. - When you require a flexible configuration that allows for custom pipelines, supporting text extraction, tokenization, and multilingual text processing. ### Choose llama-hub if… - llama-hub is primarily Jupyter Notebook; datatrove is Python. - License: llama-hub is MIT, datatrove is Apache-2.0. - Tags unique to llama-hub: community-driven, jupyter-notebook, langchain, llamaindex. - Community-specific features require engagement with community ## When NOT to use datatrove - Avoid datatrove if you are not working within Python 3.10+, as it is not compatible with earlier versions. - Do not use if you require real-time data processing functionalities that go beyond the package's current capabilities, such as streaming data handling. ## When NOT to use llama-hub - Limited support if the community lacks activity - Not suitable without familiarity with Poetry for dependency management ## Common questions ### What is the difference between datatrove and llama-hub? datatrove: Platform-agnostic customizable pipeline processing blocks for data processing and transformation.. llama-hub: A library of data loaders for LLMs made by the community. See the comparison table for live GitHub stats and shared categories. ### When should I choose datatrove over llama-hub? Choose datatrove over llama-hub when datatrove is primarily Python; llama-hub is Jupyter Notebook; License: datatrove is Apache-2.0, llama-hub is MIT; Tags unique to datatrove: data-processing, distributed-computing, file-formats-support, pipelines; Also covers Inference & Serving; When you require a flexible configuration that allows for custom pipelines, supporting text extraction, tokenization, and multilingual text processing. ### When should I choose llama-hub over datatrove? Choose llama-hub over datatrove when llama-hub is primarily Jupyter Notebook; datatrove is Python; License: llama-hub is MIT, datatrove is Apache-2.0; Tags unique to llama-hub: community-driven, jupyter-notebook, langchain, llamaindex; Community-specific features require engagement with community. ### When should I avoid datatrove? Avoid datatrove if you are not working within Python 3.10+, as it is not compatible with earlier versions. Do not use if you require real-time data processing functionalities that go beyond the package's current capabilities, such as streaming data handling. ### When should I avoid llama-hub? Limited support if the community lacks activity Not suitable without familiarity with Poetry for dependency management ### Is datatrove or llama-hub more popular on GitHub? llama-hub has more GitHub stars (3,469 vs 3,250). Stars measure visibility, not whether either tool fits your constraints. ### Are datatrove and llama-hub open source? Yes - both are open-source projects on GitHub (datatrove: Apache-2.0, llama-hub: MIT). ### Where can I find alternatives to datatrove or llama-hub? GraphCanon lists graph-backed alternatives at [datatrove alternatives](/tools/huggingface-datatrove/alternatives) and [llama-hub alternatives](/tools/run-llama-llama-hub/alternatives) ([datatrove markdown twin](/tools/huggingface-datatrove/alternatives.md), [llama-hub markdown twin](/tools/run-llama-llama-hub/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/huggingface-datatrove-vs-run-llama-llama-hub.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, datatrove or llama-hub? datatrove: Very active. llama-hub: Archived. 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 datatrove and llama-hub? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [datatrove trust report](/tools/huggingface-datatrove/trust); [llama-hub trust report](/tools/run-llama-llama-hub/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=huggingface-datatrove`](/api/graphcanon/graph?tool=huggingface-datatrove) - 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/_