{"data":{"slug":"quiltdata-quilt","name":"quilt","tagline":"Scientific Data Management Platform on AWS for managing data packages","github_url":"https://github.com/quiltdata/quilt","owner":"quiltdata","repo":"quilt","owner_avatar_url":"https://avatars.githubusercontent.com/u/17112125?v=4","primary_language":"TypeScript","stars":1370,"forks":89,"topics":["data","data-engineering","data-version-control","data-versioning","parquet","python","serialization"],"archived":false,"github_pushed_at":"2026-09-27T21:03:24+00:00","maintenance_label":"Very active","stars_delta_30d":3,"url":"https://www.graphcanon.com/tools/quiltdata-quilt","markdown_url":"https://www.graphcanon.com/tools/quiltdata-quilt.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/quiltdata-quilt","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=quiltdata-quilt","description":"Quilt is a Scientific Data Management Platform on AWS that helps teams and AI find, trust, and reuse data through deeply versioned, context-rich data packages.","homepage_url":"https://quilt.bio","license":"Apache-2.0","open_issues":119,"watchers":14,"ai_summary":"Quilt is a platform designed to help teams manage scientific and AI-related datasets by providing deep version control and context-rich data packages.","readme_excerpt":"## Quick Start for Contributors\n\n1. Clone and create a branch:\n\n   ```bash\n   git clone https://github.com/quiltdata/quilt\n   cd quilt\n   git checkout -b my-change\n   ```\n\n2. Install Python task runner:\n\n   ```bash\n   # macOS/Linux\n   curl -LsSf https://astral.sh/uv/install.sh | sh\n   ```\n\n3. Run Python tests:\n\n   ```bash\n   cd api/python\n   uv run poe test\n   ```\n\n4. Run catalog locally:\n\n   ```bash\n   cd catalog\n   npm install\n   npm start\n   ```\n\nFor full setup, testing, and release steps, see [`docs/CONTRIBUTING.md`](docs/CONTRIBUTING.md).","github_created_at":"2017-02-10T02:46:03+00:00","created_at":"2026-07-11T23:27:32.946259+00:00","updated_at":"2026-09-28T06:00:26.011177+00:00","categories":[{"slug":"data-retrieval","name":"Data & Retrieval","url":"https://www.graphcanon.com/categories/data-retrieval","markdown_url":"https://www.graphcanon.com/categories/data-retrieval.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/data-retrieval"}],"tags":[{"slug":"data-engineering","name":"data-engineering"},{"slug":"data-version-control","name":"data-version-control"},{"slug":"data-versioning","name":"data-versioning"},{"slug":"parquet","name":"parquet"},{"slug":"python","name":"python"},{"slug":"serialization","name":"serialization"}],"trust":{"provenance":{"is_fork":false,"github_id":81518954,"owner_type":"Organization","methodology":"github_public_v1","parent_repo":null,"near_duplicate_slugs":[]},"computed_at":"2026-09-28T06:00:25.088Z","maintenance":{"label":"Very active","score":96,"methodology":"github_public_v1","releases_90d":0,"days_since_push":0,"last_release_at":"2020-10-15T04:53:55Z","stars_delta_30d":3,"open_issues_delta_30d":-24},"security_summary":{"status":"no_lockfile","scanner":null,"low_count":0,"high_count":0,"last_scan_at":"2026-07-11T23:27:34.674Z","medium_count":0,"scan_profile":"none","critical_count":0}},"capability_facts":{"scan":{"source":"repo_scan","observed_at":"2026-09-28T06:00:25.593Z"},"languages":{"value":["typescript"],"source":"github.language","observed_at":"2026-09-28T06:00:25.593Z"},"license_spdx":{"value":"Apache-2.0","source":"github.license","observed_at":"2026-09-28T06:00:25.593Z"}},"decision_facts":{"hosting":null,"pricing":null,"requirements":null,"constraints":null,"when_to_use":["When your team requires in-depth version control for complex scientific datasets, ensuring that every change to the dataset is tracked and documented.","If you are working with machine learning projects where maintaining historical versions of data is crucial for reproducing results or debugging models.","For data teams aiming to improve collaboration by providing a centralized hub for finding and reusing well-documented and version-controlled datasets."],"when_not_to_use":["Not recommended if you prefer on-premises solutions over AWS-hosted services, as Quilt operates exclusively within the Amazon Web Services ecosystem.","If your project involves handling simple and static datasets where traditional CVS tools suffice. The overhead of using a specialized solution like Quilt might not justify its use.","Teams with limited experience in data engineering or with less sophisticated dataset requirements may find Quilt's robust features overly complex, potentially leading to underutilization."],"source":"enrich:decision_facts","observed_at":"2026-07-14T18:16:49.308Z"},"constraint_facets":null,"decision_summary":[{"label":"Adopt for","value":"Quilt is a platform focused on managing scientific and AI-related datasets through detailed version control and context-rich data packages hosted on AWS."}]}}