{"data":{"slug":"infiniflow-infinity","name":"infinity","tagline":"AI-native database for LLM applications offering fast hybrid search capabilities.","github_url":"https://github.com/infiniflow/infinity","owner":"infiniflow","repo":"infinity","owner_avatar_url":"https://avatars.githubusercontent.com/u/69962740?v=4","primary_language":"C++","stars":4675,"forks":437,"topics":["ai-native","approximate-nearest-neighbor-search","bm25","cpp20","cpp20-modules","embedding","full-text-search","hnsw","hybrid-search","information-retrival","multi-vector","nearest-neighbor-search","rag","search-engine","tensor-database","vector","vector-database","vector-search","vectordatabase"],"archived":false,"github_pushed_at":"2026-08-17T13:43:09+00:00","maintenance_label":"Very active","stars_delta_30d":51,"url":"https://www.graphcanon.com/tools/infiniflow-infinity","markdown_url":"https://www.graphcanon.com/tools/infiniflow-infinity.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/infiniflow-infinity","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=infiniflow-infinity","description":"The AI-native database built for LLM applications, providing incredibly fast hybrid search of dense vector, sparse vector, tensor (multi-vector), and full-text.","homepage_url":"https://infiniflow.org","license":"Apache-2.0","open_issues":64,"watchers":43,"ai_summary":"Infiniflow/infinity is an AI-native database designed to support large language model (LLM) applications by enabling extremely rapid hybrid searches across dense vector, sparse vector, tensor, and full-text data types.","readme_excerpt":"### Install Infinity server\n\n#### Linux x86_64 & MacOS x86_64\n\n```bash\nsudo mkdir -p /var/infinity && sudo chown -R $USER /var/infinity\ndocker pull infiniflow/infinity:nightly\ndocker run -d --name infinity -v /var/infinity/:/var/infinity --ulimit nofile=500000:500000 --network=host infiniflow/infinity:nightly\n```\n#### Windows\n\nIf you are on Windows 10+, you must enable WSL or WSL2 to deploy Infinity using Docker. Suppose you've installed Ubuntu in WSL2:\n\n1. Follow [this](https://learn.microsoft.com/en-us/windows/wsl/systemd) to enable systemd inside WSL2.\n2. Install docker-ce according to the [instructions here](https://docs.docker.com/engine/install/ubuntu).\n3. If you have installed Docker Desktop version 4.29+ for Windows: **Settings** **>** **Features in development**, then select **Enable host networking**.\n4. Pull the Docker image and start Infinity: \n\n   ```bash\n   sudo mkdir -p /var/infinity && sudo chown -R $USER /var/infinity\n   docker pull infiniflow/infinity:nightly\n   docker run -d --name infinity -v /var/infinity/:/var/infinity --ulimit nofile=500000:500000 --network=host infiniflow/infinity:nightly\n   ```\n\n---\n\n### Install Infinity client\n\n```\npip install infinity-sdk==0.7.3\n```","github_created_at":"2022-07-18T13:52:38+00:00","created_at":"2026-07-07T17:43:54.895949+00:00","updated_at":"2026-08-21T06:02:12.977829+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"},{"slug":"vector-databases","name":"Vector Databases","url":"https://www.graphcanon.com/categories/vector-databases","markdown_url":"https://www.graphcanon.com/categories/vector-databases.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/vector-databases"}],"tags":[{"slug":"ai-native","name":"ai-native"},{"slug":"approximate-nearest-neighbor-search","name":"approximate-nearest-neighbor-search"},{"slug":"bm25","name":"bm25"},{"slug":"cpp20","name":"cpp20"},{"slug":"embedding","name":"embedding"},{"slug":"full-text-search","name":"full-text-search"},{"slug":"hnsw","name":"hnsw"},{"slug":"hybrid-search","name":"hybrid-search"}],"trust":{"provenance":{"is_fork":false,"github_id":515204860,"owner_type":"Organization","methodology":"github_public_v1","parent_repo":null,"near_duplicate_slugs":[]},"computed_at":"2026-08-21T06:02:12.204Z","maintenance":{"label":"Very active","score":96,"methodology":"github_public_v1","releases_90d":3,"days_since_push":3,"last_release_at":"2026-08-06T04:35:14Z","stars_delta_30d":51,"open_issues_delta_30d":-2},"security_summary":{"status":"no_lockfile","scanner":null,"low_count":0,"high_count":0,"last_scan_at":"2026-07-11T11:24:37.077Z","medium_count":0,"scan_profile":"none","critical_count":0}},"capability_facts":{"scan":{"source":"repo_scan","observed_at":"2026-08-21T06:02:12.672Z"},"languages":{"value":["c++","python"],"source":"github.language+pyproject.toml","observed_at":"2026-08-21T06:02:12.672Z"},"license_spdx":{"value":"Apache-2.0","source":"github.license","observed_at":"2026-08-21T06:02:12.672Z"}},"decision_facts":{"hosting":null,"pricing":null,"requirements":null,"constraints":null,"when_to_use":["When your application requires rapid hybrid search capabilities across multiple data types including tensors and full texts.","For projects that need to integrate closely with large language models using AI-native technologies."],"when_not_to_use":["If your project does not benefit from fast hybrid search features or if you prefer not to use an AI-native database solution.","When support for only dense vectors is sufficient, and the added complexity of supporting tensors and full texts is unnecessary."],"source":"enrich:decision_facts","observed_at":"2026-07-14T20:34:54.230Z"},"constraint_facets":null,"decision_summary":[{"label":"Adopt for","value":"Designed for high-speed hybrid searches in LLM applications, infinity supports dense vector, sparse vector, tensor, and full-text data types."}]}}