{
  "id": "knowledge-fabric-impl:milvus-fabric",
  "_kind": "KnowledgeFabricImpl",
  "_file": "agent-stack/knowledge-fabric-impls/vector-store-fabrics.yaml",
  "_cluster": "agent-stack",
  "attributes": {
    "displayName": "Milvus as Knowledge Fabric",
    "description": "Milvus as a distributed, GPU-accelerated knowledge fabric. Designed for\nbillion-scale similarity search with multiple index types (IVF, HNSW,\nDiskANN), hybrid scalar-vector queries, and multi-vector search. Separate\nstorage and compute scaling for elastic deployments. Partition keys and\ntime travel features support multi-tenant knowledge isolation and\ntemporal knowledge queries. Zilliz Cloud offers managed deployment.\nAs a knowledge fabric, Milvus is the choice for enterprise-scale\nknowledge bases requiring high-throughput vector operations.\n",
    "knowledgeFileFormats": [
      "embeddings",
      "document-chunks"
    ],
    "retrievalStrategy": "semantic-search",
    "knowledgePersistence": "distributed-vector-store",
    "knowledgeScopes": [
      "organization",
      "enterprise"
    ],
    "autoExtractionSupport": false,
    "notes": "Milvus's time travel feature is unique among vector databases — it allows\nquerying the knowledge base as it existed at a past point in time. This\nis valuable for knowledge fabric auditing and understanding how\norganizational knowledge evolved. The distributed architecture handles\nbillion-scale collections but requires more operational investment.\n"
  },
  "outgoingEdges": [
    {
      "from": "knowledge-fabric-impl:milvus-fabric",
      "to": "layer:12-knowledge-fabric",
      "kind": "realizes",
      "attributes": {}
    },
    {
      "from": "knowledge-fabric-impl:milvus-fabric",
      "to": "tool:milvus",
      "kind": "integrates_with",
      "attributes": {}
    }
  ],
  "incomingEdges": []
}