{"data":{"slug":"logicalclocks-hopsworks","name":"hopsworks","tagline":"Data-Intensive AI platform with Feature Store","github_url":"https://github.com/logicalclocks/hopsworks","owner":"logicalclocks","repo":"hopsworks","owner_avatar_url":"https://avatars.githubusercontent.com/u/26795543?v=4","primary_language":"Java","stars":1302,"forks":160,"topics":["aws","azure","data-science","feature-engineering","feature-management","feature-store","gcp","governance","hopsworks","kserve","machine-learning","ml","mlops","model-serving","pyspark","python","serverless"],"archived":false,"github_pushed_at":"2025-02-10T05:53:39+00:00","maintenance_label":"Dormant","url":"https://www.graphcanon.com/tools/logicalclocks-hopsworks","markdown_url":"https://www.graphcanon.com/tools/logicalclocks-hopsworks.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/logicalclocks-hopsworks","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=logicalclocks-hopsworks","description":"Hopsworks - Data-Intensive AI platform with a Feature Store","homepage_url":"https://hopsworks.ai","license":"AGPL-3.0","open_issues":16,"watchers":33,"ai_summary":"Hopsworks is an ML platform supporting data management and model serving across multiple cloud providers including AWS, Azure, and GCP.","readme_excerpt":"# Quick Install\nGet up and running with a single command:\n```bash\ncurl -O https://raw.githubusercontent.com/logicalclocks/hopsworks-k8s-installer/master/install-hopsworks.py\npython3 install-hopsworks.py\n```\n\n\n<a name=\"what\"></a>\n\n---\n\n### **Requirements**\nYou need at least one server or virtual machine on which Hopsworks will be installed with at least the following specification:\n- Centos/RHEL 8.x or Ubuntu 22.04;\n- at least 32GB RAM,\n- at least 8 CPUs,\n- 100 GB of free hard-disk space,\n- a UNIX user account with sudo privileges.\n<br />\n\n<a name=\"docs\"></a>","github_created_at":"2018-07-26T08:13:34+00:00","created_at":"2026-07-11T23:28:44.134512+00:00","updated_at":"2026-08-03T18:00:43.236546+00:00","categories":[{"slug":"evaluation-observability","name":"Evaluation & Observability","url":"https://www.graphcanon.com/categories/evaluation-observability","markdown_url":"https://www.graphcanon.com/categories/evaluation-observability.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/evaluation-observability"},{"slug":"inference-serving","name":"Inference & Serving","url":"https://www.graphcanon.com/categories/inference-serving","markdown_url":"https://www.graphcanon.com/categories/inference-serving.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/inference-serving"},{"slug":"model-training","name":"Model Training","url":"https://www.graphcanon.com/categories/model-training","markdown_url":"https://www.graphcanon.com/categories/model-training.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/model-training"}],"tags":[{"slug":"aws","name":"aws"},{"slug":"azure","name":"azure"},{"slug":"feature-store","name":"feature-store"},{"slug":"gcp","name":"gcp"},{"slug":"mlops","name":"mlops"},{"slug":"model-serving","name":"model-serving"},{"slug":"pyspark","name":"pyspark"}],"trust":{"provenance":{"is_fork":false,"github_id":142410331,"owner_type":"Organization","methodology":"github_public_v1","parent_repo":null,"near_duplicate_slugs":[]},"computed_at":"2026-08-03T18:00:42.459Z","maintenance":{"label":"Dormant","score":18,"methodology":"github_public_v1","releases_90d":0,"days_since_push":539,"last_release_at":"2024-03-02T16:18:26Z"},"security_summary":{"status":"no_lockfile","scanner":null,"low_count":0,"high_count":0,"last_scan_at":"2026-07-11T23:28:46.680Z","medium_count":0,"scan_profile":"none","critical_count":0}},"capability_facts":{"scan":{"source":"repo_scan","observed_at":"2026-08-03T18:00:42.919Z"},"languages":{"value":["java"],"source":"github.language","observed_at":"2026-08-03T18:00:42.919Z"},"license_spdx":{"value":"AGPL-3.0","source":"github.license","observed_at":"2026-08-03T18:00:42.919Z"}},"decision_facts":{"hosting":null,"pricing":null,"requirements":null,"constraints":null,"when_to_use":["When project requirements include a comprehensive feature store for AI applications","For teams targeting multi-cloud deployments with strong data governance needs"],"when_not_to_use":["If developers prefer a tool requiring less computational resources to install","In scenarios where the preferred language is not Java and compatibility is an issue"],"source":"enrich:decision_facts","observed_at":"2026-07-17T01:04:36.180Z"},"constraint_facets":null,"decision_summary":[{"label":"Adopt for","value":"Hopsworks, an ML platform with robust data management and model serving capabilities, supports multiple cloud environments like AWS, Azure, and GCP."}]}}