{
  "id": "knowledge-fabric-impl:qdrant-fabric",
  "_kind": "KnowledgeFabricImpl",
  "_file": "agent-stack/knowledge-fabric-impls/vector-store-fabrics.yaml",
  "_cluster": "agent-stack",
  "attributes": {
    "displayName": "Qdrant as Knowledge Fabric",
    "description": "Qdrant as a performance-focused knowledge fabric. Rust-native vector\nsimilarity search engine with payload-based filtering alongside vector\nsearch, quantization for memory efficiency, and distributed deployment.\ngRPC and REST APIs with clients for Python, TypeScript, Go, and Rust.\nSnapshot and recovery features support knowledge fabric durability. As a\nknowledge fabric backend, Qdrant excels where query latency and resource\nefficiency are critical constraints.\n",
    "knowledgeFileFormats": [
      "embeddings",
      "document-chunks"
    ],
    "retrievalStrategy": "semantic-search",
    "knowledgePersistence": "vector-store",
    "knowledgeScopes": [
      "project",
      "organization"
    ],
    "autoExtractionSupport": false,
    "notes": "Qdrant's payload indexing enables rich metadata filtering without\nsacrificing vector search performance. Snapshot recovery ensures knowledge\nfabric durability across restarts. The Rust implementation provides\npredictable latency and memory usage, making Qdrant a strong choice\nfor latency-sensitive knowledge retrieval applications.\n"
  },
  "outgoingEdges": [
    {
      "from": "knowledge-fabric-impl:qdrant-fabric",
      "to": "layer:12-knowledge-fabric",
      "kind": "realizes",
      "attributes": {}
    },
    {
      "from": "knowledge-fabric-impl:qdrant-fabric",
      "to": "tool:qdrant",
      "kind": "integrates_with",
      "attributes": {}
    }
  ],
  "incomingEdges": []
}