--- title: "datasets vs lakeFS" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/huggingface-datasets-vs-treeverse-lakefs" tools: ["huggingface-datasets", "treeverse-lakefs"] --- # datasets vs lakeFS *GraphCanon updated Aug 3, 2026* ## Verdict Pick datasets if datasets is the largest hub of ready-to-use datasets for AI models, offering extensive collection and fast, easy-to-use data manipulation tools; pick lakeFS if lakeFS provides Git-like functionality for managing versions of data in a data lake, compatible with storage solutions like S3 and Azure. [datasets](https://huggingface.co/docs/datasets) reports 22k GitHub stars, 3.3k forks, and 1.2k open issues, last pushed Jul 30, 2026. [lakeFS](https://docs.lakefs.io) has 5.5k stars, 472 forks, and 437 open issues, last pushed Aug 3, 2026. Figures are from public GitHub metadata via [datasets's repository](https://github.com/huggingface/datasets) and [lakeFS's repository](https://github.com/treeverse/lakeFS). | | [datasets](/tools/huggingface-datasets.md) | [lakeFS](/tools/treeverse-lakefs.md) | | --- | --- | --- | | Tagline | Largest hub of ready-to-use datasets for AI models | Data version control for your data lake | | Stars | 21,791 | 5,480 | | Forks | 3,322 | 472 | | Open issues | 1,179 | 437 | | Language | Python | Go | | Adopt for | datasets is the largest hub of ready-to-use datasets for AI models, offering extensive collection and fast, easy-to-use data manipulation tools. | lakeFS provides Git-like functionality for managing versions of data in a data lake, compatible with storage solutions like S3 and Azure. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | Apache-2.0 | | Categories | Data & Retrieval | Data & Retrieval | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [datasets](/tools/huggingface-datasets.md) | [lakeFS](/tools/treeverse-lakefs.md) | | --- | --- | --- | | Open issues (now) | 1.2k | 437 | | Full report | [trust report](/tools/huggingface-datasets/trust.md) | [trust report](/tools/treeverse-lakefs/trust.md) | ## Shared compatibility - **Python**: [datasets](/tools/huggingface-datasets.md) - Python runtime; [lakeFS](/tools/treeverse-lakefs.md) - Python runtime ## Decision facts: datasets - **Adopt for:** datasets is the largest hub of ready-to-use datasets for AI models, offering extensive collection and fast, easy-to-use data manipulation tools. ## Decision facts: lakeFS - **Adopt for:** lakeFS provides Git-like functionality for managing versions of data in a data lake, compatible with storage solutions like S3 and Azure. ## Choose when ### Choose datasets if… - datasets is primarily Python; lakeFS is Go. - Tags unique to datasets: ai, artificial-intelligence, dataset-hub, datasets. - Use datasets if you need access to a large number of ready-to-use datasets specifically suited for training AI models. ### Choose lakeFS if… - lakeFS is primarily Go; datasets is Python. - Tags unique to lakeFS: apache-spark, aws-s3, azure-blob-storage, data-engineering. - lakeFS ships Docker support for self-hosted deployment. - When you need version control for large-scale datasets stored in a data lake, similar to how codebases are managed with Git. ## When NOT to use datasets - Avoid datasets if the specific type of dataset required for your project is not included in their extensive collection. - Do not use datasets if you prefer less integration with popular machine learning frameworks like PyTorch or TensorFlow, as this tool heavily integrates with these platforms. ## When NOT to use lakeFS - If your use case involves managing small files or datasets that do not benefit from a Git-like history for data changes due to overhead. - For situations where compliance requirements preclude open-source solutions or those under the Apache 2.0 license, as lakeFS may not meet these specific needs. ## Common questions ### What is the difference between datasets and lakeFS? datasets: Largest hub of ready-to-use datasets for AI models. lakeFS: Data version control for your data lake. See the comparison table for live GitHub stats and shared categories. ### When should I choose datasets over lakeFS? Choose datasets over lakeFS when datasets is primarily Python; lakeFS is Go; Tags unique to datasets: ai, artificial-intelligence, dataset-hub, datasets; Use datasets if you need access to a large number of ready-to-use datasets specifically suited for training AI models. ### When should I choose lakeFS over datasets? Choose lakeFS over datasets when lakeFS is primarily Go; datasets is Python; Tags unique to lakeFS: apache-spark, aws-s3, azure-blob-storage, data-engineering; lakeFS ships Docker support for self-hosted deployment; When you need version control for large-scale datasets stored in a data lake, similar to how codebases are managed with Git. ### When should I avoid datasets? Avoid datasets if the specific type of dataset required for your project is not included in their extensive collection. Do not use datasets if you prefer less integration with popular machine learning frameworks like PyTorch or TensorFlow, as this tool heavily integrates with these platforms. ### When should I avoid lakeFS? If your use case involves managing small files or datasets that do not benefit from a Git-like history for data changes due to overhead. For situations where compliance requirements preclude open-source solutions or those under the Apache 2.0 license, as lakeFS may not meet these specific needs. ### Is datasets or lakeFS more popular on GitHub? datasets has more GitHub stars (21,791 vs 5,480). Stars measure visibility, not whether either tool fits your constraints. ### Are datasets and lakeFS open source? Yes - both are open-source projects on GitHub (datasets: Apache-2.0, lakeFS: Apache-2.0). ### Where can I find alternatives to datasets or lakeFS? GraphCanon lists graph-backed alternatives at [datasets alternatives](/tools/huggingface-datasets/alternatives) and [lakeFS alternatives](/tools/treeverse-lakefs/alternatives) ([datasets markdown twin](/tools/huggingface-datasets/alternatives.md), [lakeFS markdown twin](/tools/treeverse-lakefs/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-datasets-vs-treeverse-lakefs.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, datasets or lakeFS? datasets: Very active. lakeFS: 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 datasets and lakeFS? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [datasets trust report](/tools/huggingface-datasets/trust); [lakeFS trust report](/tools/treeverse-lakefs/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=huggingface-datasets`](/api/graphcanon/graph?tool=huggingface-datasets) - 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/_