{
  "id": "tool:chromadb",
  "_kind": "Tool",
  "_file": "domain/tools/memory-systems.yaml",
  "_cluster": "domain",
  "attributes": {
    "displayName": "Chroma",
    "homepageUrl": "https://www.trychroma.com",
    "kind": "other",
    "description": "Open-source embedding database purpose-built for AI applications.\nStores documents with embeddings and metadata, supports filtering,\nand returns nearest-neighbor results. Runs in-memory, as a local\npersistent store, or as a client-server deployment. First-class\nintegrations with LangChain, LlamaIndex, and OpenAI make it a\ncommon default for prototyping RAG pipelines.\n"
  },
  "outgoingEdges": [
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      "to": "language:python",
      "kind": "belongs_to_language"
    },
    {
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      "to": "skill-area:retrieval-augmented-generation",
      "kind": "tool_used_by",
      "attributes": {}
    },
    {
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    {
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      "kind": "alternative_to",
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      }
    },
    {
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      "kind": "alternative_to",
      "attributes": {
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      }
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      }
    },
    {
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      "to": "tool:milvus",
      "kind": "alternative_to",
      "attributes": {
        "comparison": "Vector databases — Chroma targets prototyping; Milvus targets billion-scale"
      }
    }
  ],
  "incomingEdges": [
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    },
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      }
    },
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      }
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      }
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      }
    },
    {
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    }
  ]
}