spb/tools-spboucher-ai

1{2  "aliases": [],3  "workflows": [4    "RAG backend that embeds documents on ingest",5    "Hybrid search for product or document catalogs",6    "Multi-tenant SaaS search with per-customer isolation"7  ],8  "advantages": [9    "Embedding generation handled by modules",10    "Hybrid search in one query",11    "Managed cloud and self-hosted options"12  ],13  "limitations": [14    "Enterprise features are proprietary (wl directory)",15    "Schema and module configuration add setup effort",16    "GraphQL API has a learning curve"17  ],18  "prerequisites": [19    "Docker, Kubernetes or Weaviate Cloud",20    "API keys for external vectorizer modules if used"21  ],22  "audiences": [23    "Developers building RAG and semantic search",24    "Teams needing multi-tenant vector search"25  ],26  "alternatives": [27    "qdrant",28    "milvus",29    "pgvector",30    "chroma",31    "pinecone"32  ],33  "tags": [34    "vector-search",35    "embeddings",36    "rag",37    "self-hosted",38    "api",39    "go"40  ],41  "use_cases": [42    "build-agents",43    "semantic-search"44  ],45  "operating_systems": [46    "linux",47    "macos",48    "windows"49  ],50  "deployment_models": [51    "on-premises",52    "managed-cloud"53  ],54  "integrations": [55    "OpenAI",56    "Cohere",57    "Hugging Face",58    "Ollama",59    "LangChain",60    "LlamaIndex",61    "Haystack"62  ],63  "data_formats": [64    "JSON objects",65    "Backups to S3/GCS/filesystem"66  ],67  "languages": [68    "Go",69    "Python",70    "TypeScript",71    "Java"72  ],73  "self_hostable": true,74  "discovery_method": "editorial-research",75  "depth": "standard",76  "editorial_status": "reviewed",77  "visibility": "public",78  "featured": false,79  "author": "batch-D",80  "slug": "weaviate",81  "name": "Weaviate",82  "vendor": {83    "name": "Weaviate B.V.",84    "slug": "weaviate-bv",85    "website": "https://weaviate.io/"86  },87  "homepage_url": "https://weaviate.io/",88  "docs_url": "https://docs.weaviate.io/weaviate",89  "repo_url": "https://github.com/weaviate/weaviate",90  "license_url": "https://github.com/weaviate/weaviate/blob/main/LICENSE",91  "pricing_url": "https://weaviate.io/pricing",92  "pricing_checked_at": "2026-11-02",93  "product_type": "database",94  "product_status": "active",95  "summary": "Open-source vector database in Go with pluggable vectorizer modules, hybrid BM25 and vector search, multi-tenancy and a managed cloud",96  "description": "Weaviate is a vector database written in Go by Weaviate B.V. Objects are stored in classes (collections) with a schema, each carrying one or more vectors; search combines HNSW nearest-neighbor retrieval with BM25 keyword scoring in a single hybrid query and supports filters, grouping and generative or reranking modules. A distinguishing feature is the module system: vectorizer modules call OpenAI, Cohere, Google, Hugging Face or local models so that the database embeds objects on write and queries on read, which removes that step from application code.\n\nThe server exposes REST, gRPC and GraphQL APIs with clients for Python, TypeScript, Go and Java, supports multi-tenancy with per-tenant shards, replication and horizontal scaling, and offers vector compression options. Most of the repository is BSD-3-Clause; code under the wl directory is proprietary and enabled with an enterprise license key. Weaviate Cloud provides managed serverless and dedicated clusters.\n\nWeaviate suits teams who want embedding generation, hybrid retrieval and RAG helpers in one service. Trade-offs are a heavier schema model than minimal stores, dependence on module configuration for embeddings, and enterprise-only features behind the commercial license.",97  "capabilities": [98    "HNSW vector search with filters and hybrid BM25 fusion",99    "Vectorizer, reranker and generative modules calling external or local models",100    "REST, gRPC and GraphQL APIs",101    "Multi-tenancy with isolated shards",102    "Replication and horizontal scaling",103    "Vector compression (PQ, BQ, SQ)"104  ],105  "categories": [106    {107      "slug": "vector-databases",108      "primary": true109    },110    {111      "slug": "embeddings-vector-search"112    }113  ],114  "execution_modes": [115    "self-hosted",116    "cloud"117  ],118  "interfaces": [119    "api",120    "sdk"121  ],122  "source_model": "mixed",123  "license_spdx": "BSD-3-Clause",124  "pricing_model": [125    "open-source",126    "freemium",127    "usage-based",128    "enterprise"129  ],130  "sources": [131    {132      "url": "https://weaviate.io/",133      "type": "official_site",134      "supports": [135        "name",136        "summary"137      ],138      "checked_at": "2026-11-02",139      "title": "Weaviate"140    },141    {142      "url": "https://docs.weaviate.io/weaviate",143      "type": "official_docs",144      "supports": [145        "capabilities",146        "interfaces",147        "languages"148      ],149      "checked_at": "2026-11-02",150      "title": "Weaviate Documentation"151    },152    {153      "url": "https://github.com/weaviate/weaviate/blob/main/LICENSE",154      "type": "license_page",155      "supports": [156        "license_spdx",157        "source_model"158      ],159      "checked_at": "2026-11-02",160      "title": "Weaviate LICENSE",161      "note": "BSD-3-Clause outside the wl directory; wl directory is proprietary enterprise code"162    },163    {164      "url": "https://weaviate.io/pricing",165      "type": "pricing_page",166      "supports": [167        "pricing_model"168      ],169      "checked_at": "2026-11-02",170      "title": "Weaviate pricing"171    },172    {173      "url": "https://github.com/weaviate/weaviate",174      "type": "repository",175      "supports": [176        "repo_url"177      ],178      "checked_at": "2026-11-02",179      "title": "weaviate/weaviate"180    }181  ],182  "confidence": "high"183}184