Which vector database should I pick if our startup is building an internal search tool this month?
Download run
Fan-out diagram
The searches the AI actually ran for this prompt.
SEED QUERY
Which vector database should I pick if our startup is building an internal search tool this month?
2 real searches · 1 real-search pass
Badge and edge weight = share of passes that produced the query. Hover a query for its intent and routing format.
Query classes
Google's semantic query class for every sub-query: what kind of answer each search is after, simulated vs real.
ChatGPT real searches (2)
Classes come from the query-classifier (a local Laya model). 1 of 2 calls are low-confidence (under 50%) — hover a query in the table to see its confidence.
Searches and sources
ChatGPT2 real searches · gpt-6
2026 pgvector Qdrant Pinecone Weaviate official docs filtering hybrid search pricing deployment updates Google ↗
2026 vector database comparison pgvector Qdrant Pinecone Weaviate internal enterprise search tradeoffs Google ↗
- Website · qdrant.tech
- Documentation · qdrant.tech
- GitHub and documentation · github.com
- Website · pinecone.io
- Website · weaviate.io
- Documentation · docs.weaviate.io
- Filtering in Vector Search: When to Use What · qdrant.tech
- Overview · qdrant.tech
- Hybrid search · docs.weaviate.io
Queries
2 queries · click a column to sort
| Query / type | Search | Intent | Query class | Routing format | Cluster | Freq ↓ | Weight |
|---|---|---|---|---|---|---|---|
2026 pgvector Qdrant Pinecone Weaviate official docs filtering hybrid search pricing deployment updates OBSERVED | Google ↗ AI Mode ↗ | — | Comparison | — | — | 1x of 1 | |
2026 vector database comparison pgvector Qdrant Pinecone Weaviate internal enterprise search tradeoffs OBSERVED | Google ↗ AI Mode ↗ | — | Comparison | — | — | 1x of 1 |