# Vector databases for enterprise buyers: what AI models recommend, November 2026

Gane Index, November 2026 Edition. Asked as "vector database" and as "vector search database for AI applications", six framings each, to fourteen models with search on, on behalf of an enterprise B2B company. Page: https://www.gane.ai/index/it/it-data/vector-databases/2026-11/enterprise

**Standing:** Pinecone leads with 45% of first choices; verdict clear leader. 55 first choices across the direct, paraphrase, budget and scale prompts.

## First-choice share

| Rank | Product | Share | Negative rate | Labels |
|---|---|---|---|---|
| 1 | [Pinecone](https://www.gane.ai/index/it/vendors/pinecone/index.md) | 45% | 26% | 77 |
| 2 | [Qdrant](https://www.gane.ai/index/it/vendors/qdrant/index.md) | 20% | 10% | 67 |
| 3 | [Weaviate](https://www.gane.ai/index/it/vendors/weaviate/index.md) | 13% | 10% | 67 |
| 4 | [pgvector](https://www.gane.ai/index/it/vendors/pgvector/index.md) | 7% | 13% | 52 |
| 5 | [Milvus](https://www.gane.ai/index/it/vendors/milvus/index.md) | 7% | 13% | 39 |
| 6 | [MongoDB Atlas Vector Search](https://www.gane.ai/index/it/vendors/mongodb-atlas-vector-search/index.md) | 4% | 0% | 15 |
| 7 | [Elasticsearch / OpenSearch](https://www.gane.ai/index/it/vendors/elasticsearch-opensearch/index.md) | 2% | 21% | 14 |
| 9 | [Milvus / Zilliz Cloud](https://www.gane.ai/index/it/vendors/milvus-zilliz-cloud/index.md) | 0% | 14% | 29 |
| 10 | [Zilliz Cloud](https://www.gane.ai/index/it/vendors/zilliz-cloud/index.md) | 0% | 0% | 17 |
| 11 | [Elasticsearch](https://www.gane.ai/index/it/vendors/elasticsearch/index.md) | 0% | 0% | 18 |
| 12 | [Azure AI Search](https://www.gane.ai/index/it/vendors/azure-ai-search/index.md) | 0% | 0% | 19 |
| 64 | [Redis Vector Search](https://www.gane.ai/index/it/vendors/redis-vector-search/index.md) | 0% | 40% | 10 |

Rank is by share of first choices among all 68 products named; products with the same share are tied, and the order among them carries no meaning. The table lists those with at least 10 labels.

## Each model's first choice on the direct prompt

- Claude Haiku 4.5: no first choice
- GPT-5.4 mini: Pinecone; alternatives MongoDB Atlas Vector Search, OpenSearch, Weaviate, pgvector
- Gemini 3.5 Flash: pgvector; alternatives Milvus / Zilliz Cloud, Pinecone, Qdrant, Weaviate
- Perplexity Sonar: Pinecone; alternatives Elasticsearch, Milvus / Zilliz Cloud, Qdrant, pgvector
- Grok 4.20: Pinecone; alternatives Amazon OpenSearch Service, Milvus / Zilliz Cloud, Qdrant, Weaviate
- Mistral Small: Pinecone; alternatives Milvus / Zilliz Cloud, Qdrant, Weaviate
- DeepSeek V4 Flash: Qdrant; alternatives Milvus / Zilliz Cloud, Pinecone
- Llama 4 Maverick: Pinecone; alternatives Milvus, Qdrant, Weaviate
- Qwen 3.7 Flash: Pinecone; alternatives Weaviate, Zilliz Cloud
- Kimi K2: Pinecone; alternatives Milvus / Zilliz Cloud, Weaviate, pgvector
- GLM 4.7 FlashX: Qdrant; alternatives Milvus / Zilliz Cloud, Pinecone, Weaviate, pgvector
- MiniMax M2.5: Pinecone, Weaviate; alternatives Milvus, Qdrant
- GPT-6 Luna: Qdrant; alternatives Pinecone, Weaviate, pgvector
- Muse Glimmer 30B: Qdrant; alternatives Milvus / Zilliz Cloud, Pinecone, Vespa, Weaviate

## Sources the answers cite

77 of 84 answers came back with a source list, from 14 of 14 models. Sites named in the most answers:

- github.com: 38 answers, 67 citations
- dev.to: 32 answers, 62 citations
- g2.com: 26 answers, 27 citations
- sganalytics.com: 22 answers, 22 citations
- atlan.com: 18 answers, 18 citations
- pinecone.io: 17 answers, 28 citations
- actian.com: 17 answers, 25 citations
- linkedin.com: 17 answers, 19 citations

Pages named in the most answers:

- https://g2.com/articles/best-vector-databases (26 answers)
- https://sganalytics.com/blog/top-vector-databases-enterprise-ai (22 answers)
- https://atlan.com/know/top-vector-databases-enterprise-ai (18 answers)
- https://dev.to/devrudals/enterprise-vector-database-2026-qdrant-vs-milvus-vs-pgvector-vs-pinecone-16a0 (13 answers)
- https://factory.fpt.ai/ai-insights/best-vector-database-comparison (12 answers)
- https://actian.com/blog/databases/how-to-evaluate-vector-databases-in-2026 (11 answers)
- https://gane.ai/index/it/it-data/vector-databases/enterprise (11 answers)
- https://github.com/exploreborders/RAG_Architecture/blob/main/docs/3-technical/vector-databases.md (11 answers)
- https://marktechpost.com/2026/05/10/best-vector-databases-in-2026-pricing-scale-limits-and-architecture-tradeoffs-across-nine-leading-systems (11 answers)
- https://milvus.io/blog/choosing-the-right-vector-database-for-your-ai-apps.md (9 answers)

## Warned against

- Pinecone: 20 of 77 labels negative. "Avoid for your use case: Pure Pinecone Serverless (usage-based with $50+ minimums; read units scale with queries/index size, leading to variable bills" (Grok 4.20, budget prompt)
- Chroma: 14 of 19 labels negative. "Simple In-Memory/In-Process Libraries for Production Scale
Examples: `Chroma`, `LanceDB` (in-memory mode)... lack the distributed fault tolerance, ACID transactions, and horizontal scaling required by large enterprises" (Qwen 3.7 Flash, negative prompt)
- Weaviate: 7 of 67 labels negative. "Avoid usage-based models (Milvus/Zilliz Cloud, Weaviate Cloud) for budget predictability" (GLM 4.7 FlashX, budget prompt)
- FAISS: 6 of 6 labels negative. "simple Python libraries like `faiss` alone... lack the distributed fault tolerance, ACID transactions, and horizontal scaling required by large enterprises" (Qwen 3.7 Flash, negative prompt)

## Movement since October 2026

Floor: 11 points of share, measured on the calibration repeat.
Same leader: Pinecone at 45%.

- Pinecone: 59% to 45%, −14. Cleared the floor by 3 points · rank 1 of 68, unchanged.
- Qdrant: 9% to 20%, +11. Inside the floor by 0 points · rank 2 of 68, unchanged.
- Weaviate: 7% to 13%, +6. Inside the floor by 5 points · rank 4 → 3 of 68.
- MongoDB Atlas Vector Search: 0% to 4%, +4. Inside the floor by 7 points · rank 13 → 6 of 68.
- Milvus: 9% to 7%, −2. Inside the floor by 9 points · rank 3 → 5 of 68.
- Elasticsearch / OpenSearch: 0% to 2%, +2. Inside the floor by 9 points · rank 14 → 7 of 68.
- Zilliz Cloud: 2% to 0%, −2. Inside the floor by 9 points · rank 6 → 10 of 68.
- Elasticsearch: 2% to 0%, −2. Inside the floor by 9 points · rank 7 → 11 of 68.
- pgvector: 7% to 7%, ±0. Inside the floor by 11 points · rank 5 → 4 of 68.
- Milvus / Zilliz Cloud: 0% to 0%, ±0. Inside the floor by 11 points · rank 11 → 9 of 68.
- Azure AI Search: 0% to 0%, ±0. Inside the floor by 11 points · rank 10 → 12 of 68.
- Redis Vector Search: 0% to 0%, ±0. Inside the floor by 11 points · rank 36 → 64 of 68.

## Record

- Method: https://www.gane.ai/index/it/methodology
- License: CC BY 4.0. Cite as Gane Index, November 2026 Edition, www.gane.ai/index/it.