# MongoDB Atlas Vector Search: how AI models rank it, November 2026

Gane Index, November 2026 Edition. Named in 7 judge labels across 1 category by 5 of 14 models. Page: https://www.gane.ai/index/it/vendors/mongodb-atlas-vector-search

## Standing by category

| Category | Share | Rank | Negative rate | Labels |
|---|---|---|---|---|
| [Vector databases](https://www.gane.ai/index/it/it-data/vector-databases/index.md) | 0% | 16 | 14% | 7 |

## What the models said for it

- "Best for: Companies already invested in PostgreSQL or MongoDB." (Qwen 3.7 Flash, Vector databases)
- "genuinely competitive for mid-scale RAG" (Claude Haiku 4.5, Vector databases)

## And against it

- "Avoid heavier enterprise options like Elasticsearch/OpenSearch or MongoDB Atlas Vector Search" (Grok 4.20, Vector databases)

## By model

| Model | First choice | Alternative | Mention | Warning | Labels |
|---|---|---|---|---|---|
| Claude Haiku 4.5 | 0 | 1 | 0 | 0 | 1 |
| GPT-5.4 mini | 0 | 0 | 0 | 0 | 0 |
| Gemini 3.5 Flash | 0 | 0 | 0 | 0 | 0 |
| Perplexity Sonar | 0 | 0 | 0 | 0 | 0 |
| Grok 4.20 | 0 | 0 | 1 | 1 | 2 |
| Mistral Small | 0 | 0 | 1 | 0 | 1 |
| DeepSeek V4 Flash | 0 | 0 | 2 | 0 | 2 |
| Llama 4 Maverick | 0 | 0 | 0 | 0 | 0 |
| Qwen 3.7 Flash | 0 | 1 | 0 | 0 | 1 |
| Kimi K2 | 0 | 0 | 0 | 0 | 0 |
| GLM 4.7 FlashX | 0 | 0 | 0 | 0 | 0 |
| MiniMax M2.5 | 0 | 0 | 0 | 0 | 0 |
| GPT-6 Luna | 0 | 0 | 0 | 0 | 0 |
| Muse Glimmer 30B | 0 | 0 | 0 | 0 | 0 |

## Sources returned with these answers

The sites and pages cited by the answers that named MongoDB Atlas Vector Search, from 26 of the 27 answers that named it (only the models that return a source list).

### Domains cited

- github.com: 14
- dev.to: 9
- linkedin.com: 8
- g2.com: 7
- atlan.com: 6
- ciopages.com: 6
- milvus.io: 6
- mongodb.com: 6 (its own site)
- pureinsights.com: 6
- sganalytics.com: 6

### Pages cited

- https://g2.com/articles/best-vector-databases: 7
- https://atlan.com/know/top-vector-databases-enterprise-ai: 6
- https://ciopages.com/buyer-guides/vector-database: 6
- https://pureinsights.com/blog/2024/comparing-vector-search-solutions-2024: 6
- https://sganalytics.com/blog/top-vector-databases-enterprise-ai: 6
- https://liveblocks.io/blog/whats-the-best-vector-database-for-building-ai-products: 5
- https://github.com/exploreborders/RAG_Architecture/blob/main/docs/3-technical/vector-databases.md: 4
- https://milvus.io/blog/choosing-the-right-vector-database-for-your-ai-apps.md: 4

## In its own words

What MongoDB Atlas Vector Search's own pages state, read 2026-09-28. Stated by the vendor, not checked by the index.

- Positioning: Build intelligent applications with vector search, hybrid search, and generative AI on the live operational data already in MongoDB. (https://www.mongodb.com/products/platform/atlas-vector-search)
- For: teams (https://www.mongodb.com/products/platform/atlas-vector-search)
- Free plan or trial: Get started for free in minutes (https://www.mongodb.com/products/platform/atlas-vector-search)
- Hosting: 125+ regions worldwide
- Customers named: Novo Nordisk

## 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.