# How do I choose a vector database for a mid-market team?

Category: Vector Databases. Intent: informational. Top brand: PostgreSQL.

Page: https://slateindex.ai/prompt/how-do-i-choose-a-vector-database-for-a-mid-market-team-bk3lkw6oo2 · data of 2026-11-02

## Brands named

| Brand | Share of engines |
|---|---|
| Pinecone | 100% |
| PostgreSQL | 100% |
| Qdrant | 100% |
| Weaviate | 100% |
| MongoDB Atlas | 67% |
| Zilliz Cloud | 33% |
| Redis | 33% |
| AWS | 33% |
| Elasticsearch | 33% |
| OpenSearch | 33% |

## Sources

- atlan.com (2)
- pinecone.io (2)
- weaviate.io (2)
- agentsurface.dev (1)
- ann-benchmarks.com (1)
- buildwithaitoday.com (1)
- dupple.com (1)
- entexis.in (1)
- firecrawl.dev (1)
- github.com (1)
- logiciel.io (1)
- milvus.io (1)
- pertamapartners.com (1)
- qdrant.tech (1)
- rework.com (1)
- semantic.io (1)
- simorconsulting.com (1)
- splunk.com (1)
- swfte.com (1)

## Definitions

- Visibility (0–100): how often and how high AI answers name the brand, weighted by position.
- Mention rate: share of collected AI answers that name the brand.
- Share of voice: the brand's mentions as a share of all brand mentions in the category.
- Citation authority: share of answers naming the brand that cite the brand's own site.

Cite as: SlateIndex, “How do I choose a vector database for a mid-market team?”, https://slateindex.ai/prompt/how-do-i-choose-a-vector-database-for-a-mid-market-team-bk3lkw6oo2, data of 2026-11-02. Licence: CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/).