Who ChatGPT recommends for vector databases.
Updated 9 October 202615 ChatGPT answers
We asked ChatGPT 5 buyer prompts 3 times each on 9 October 2026, with live web search on, and counted every product its 15 usable answers named. This page is ChatGPT alone; the full ranking compares every engine and quotes every answer.
Who ChatGPT recommends.
What this does and does not show.
- Counted from ChatGPT’s 15 usable answers of 15 planned.
- Products level on share of answers and average position share a rank: the measurement shows no difference between them.
- Counted as one product under reviewed spellings: “Chroma (ChromaDB)” as Chroma; “Milvus (Zilliz Milvus)” and “Zilliz” and “Zilliz Cloud” as Milvus; “pgvector (Postgres + pgvector)” and “pgvector (Postgres extension)” as pgvector; “Qdrant Cloud” as Qdrant; “Redis (RedisVector / Redis Stack)” as Redis; “Weaviate Cloud” as Weaviate.
- AI answers vary from run to run and with each person’s history and settings. This is what ChatGPT answered on 9 October 2026, asked fresh each time, not what every user will see.
- One engine and one month. Another engine, or next month, can name different products.
Not affiliated with or endorsed by OpenAI.How it works · Every engine for vector databases · According to Claude · According to Perplexity