--- title: "easy-dataset vs Curator" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/conardli-easy-dataset-vs-nvidia-nemo-curator" tools: ["conardli-easy-dataset", "nvidia-nemo-curator"] --- # easy-dataset vs Curator *GraphCanon updated Aug 18, 2026* ## Verdict Pick easy-dataset if easy-dataset is a JavaScript-based tool designed to simplify the creation and management of datasets for LLM fine-tuning, RAG systems, and evaluations; pick Curator if scalable toolkit for data pre-processing tailored to LLMs, featuring deduplication and quality checks. [easy-dataset](https://docs.easy-dataset.com) reports 15k GitHub stars, 1.5k forks, and 125 open issues, last pushed May 1, 2026. [Curator](https://github.com/NVIDIA-NeMo/Curator) has 1.7k stars, 306 forks, and 272 open issues, last pushed Jul 23, 2026. Figures are from public GitHub metadata via [easy-dataset's repository](https://github.com/ConardLi/easy-dataset) and [Curator's repository](https://github.com/NVIDIA-NeMo/Curator). | | [easy-dataset](/tools/conardli-easy-dataset.md) | [Curator](/tools/nvidia-nemo-curator.md) | | --- | --- | --- | | Tagline | A powerful tool for creating datasets for LLM fine-tuning, RAG, and evaluation | Scalable data pre-processing and curation toolkit for LLMs | | Stars | 14,792 | 1,681 | | Forks | 1,523 | 306 | | Open issues | 125 | 272 | | Language | JavaScript | Python | | Adopt for | Easy-dataset is a JavaScript-based tool designed to simplify the creation and management of datasets for LLM fine-tuning, RAG systems, and evaluations. | Scalable toolkit for data pre-processing tailored to LLMs, featuring deduplication and quality checks. | | Persona | - | - | | Runtime | - | - | | License | Other | Apache-2.0 | | Categories | Data & Retrieval, Model Training | Data & Retrieval, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [easy-dataset](/tools/conardli-easy-dataset.md) | [Curator](/tools/nvidia-nemo-curator.md) | | --- | --- | --- | | Maintenance | Slowing (36%) | Very active (96%) | | Days since push | 108d | 0d | | Open issues (now) | 125 | 272 | | Stars delta | +125 (30d) | Unknown | | Open issues delta | +1 (30d) | Unknown | | Owner type | User | Organization | | Full report | [trust report](/tools/conardli-easy-dataset/trust.md) | [trust report](/tools/nvidia-nemo-curator/trust.md) | ## Decision facts: easy-dataset - **Adopt for:** Easy-dataset is a JavaScript-based tool designed to simplify the creation and management of datasets for LLM fine-tuning, RAG systems, and evaluations. ## Decision facts: Curator - **Adopt for:** Scalable toolkit for data pre-processing tailored to LLMs, featuring deduplication and quality checks. ## Choose when ### Choose easy-dataset if… - easy-dataset is primarily JavaScript; Curator is Python. - License: easy-dataset is Other, Curator is Apache-2.0. - Tags unique to easy-dataset: dataset, fine-tuning, javascript, llm. - easy-dataset ships Docker support for self-hosted deployment. - - You prefer using JavaScript, as Easy-Dataset leverages this language for its setup. ### Choose Curator if… - Curator is primarily Python; easy-dataset is JavaScript. - License: Curator is Apache-2.0, easy-dataset is Other. - Tags unique to Curator: curation toolkit, data pre-processing, deduplication, llms. - You're working with NVIDIA NeMo models and require seamless integration. ## When NOT to use easy-dataset - - When you require a multi-language support beyond JavaScript, as Easy-Dataset is specifically built with JavaScript in mind. - - In cases where you do not want to use automatic initialization of databases or prefer manual setup configurations. - - If your deployment environment strictly avoids Docker images and prefers alternatives for application containerization. ## When NOT to use Curator - Your dataset doesn't align with NVIDIA hardware specifications. - You prefer data curation tools that do not emphasize semantic processing. ## Common questions ### What is the difference between easy-dataset and Curator? easy-dataset: A powerful tool for creating datasets for LLM fine-tuning, RAG, and evaluation. Curator: Scalable data pre-processing and curation toolkit for LLMs. See the comparison table for live GitHub stats and shared categories. ### When should I choose easy-dataset over Curator? Choose easy-dataset over Curator when easy-dataset is primarily JavaScript; Curator is Python; License: easy-dataset is Other, Curator is Apache-2.0; Tags unique to easy-dataset: dataset, fine-tuning, javascript, llm; easy-dataset ships Docker support for self-hosted deployment; - You prefer using JavaScript, as Easy-Dataset leverages this language for its setup. ### When should I choose Curator over easy-dataset? Choose Curator over easy-dataset when Curator is primarily Python; easy-dataset is JavaScript; License: Curator is Apache-2.0, easy-dataset is Other; Tags unique to Curator: curation toolkit, data pre-processing, deduplication, llms; You're working with NVIDIA NeMo models and require seamless integration. ### When should I avoid easy-dataset? - When you require a multi-language support beyond JavaScript, as Easy-Dataset is specifically built with JavaScript in mind. - In cases where you do not want to use automatic initialization of databases or prefer manual setup configurations. - If your deployment environment strictly avoids Docker images and prefers alternatives for application containerization. ### When should I avoid Curator? Your dataset doesn't align with NVIDIA hardware specifications. You prefer data curation tools that do not emphasize semantic processing. ### Is easy-dataset or Curator more popular on GitHub? easy-dataset has more GitHub stars (14,792 vs 1,681). Stars measure visibility, not whether either tool fits your constraints. ### Are easy-dataset and Curator open source? Yes - both are open-source projects on GitHub (easy-dataset: Other, Curator: Apache-2.0). ### Where can I find alternatives to easy-dataset or Curator? GraphCanon lists graph-backed alternatives at [easy-dataset alternatives](/tools/conardli-easy-dataset/alternatives) and [Curator alternatives](/tools/nvidia-nemo-curator/alternatives) ([easy-dataset markdown twin](/tools/conardli-easy-dataset/alternatives.md), [Curator markdown twin](/tools/nvidia-nemo-curator/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/conardli-easy-dataset-vs-nvidia-nemo-curator.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, easy-dataset or Curator? easy-dataset: Slowing. Curator: 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 easy-dataset and Curator? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [easy-dataset trust report](/tools/conardli-easy-dataset/trust); [Curator trust report](/tools/nvidia-nemo-curator/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=conardli-easy-dataset`](/api/graphcanon/graph?tool=conardli-easy-dataset) - 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/_