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Buying question

Recommend a low-latency vector search system for a workload that may grow to billions of embeddings.

Which brands each model API named when asked this question, and which pages it cited. Answer text is not published.
Snapshot Sep 12, 2026. Each category is re-run in rotation, every few weeks.

Recommendation

Kind of question

3

Model APIs

2

Brands named

15

Pages cited

Brands

Brands the answers named

Ordered by how many model APIs named the brand, then by mentions. A mention is not an endorsement or a position.
Rank#BrandModel APIsMentionsNamed by
1Vespavespa.ai23OpenAI · Google
2Redisredis.io12OpenAI

Model APIs

What each model API returned

One row per model API. The hash identifies the exact answer without publishing it.
Model APIModelBrands namedCitationsDomainsAnswer hash
OpenAIopenai/gpt-4o-miniRedis · Vespa84e0a1c5ed…75486
Anthropicanthropic/claude-haiku-4-5None named0081ceee7c…01a24
Googlegoogle/gemini-2.5-flashVespa996cf63b9a…6840e

Sources

Pages the answers cited

Hostnames come from the URLs the answers returned. Best position is the earliest place a page was cited in an answer.
DomainCited pageBest positionCited byCitations
scylladb.comhttps://scylladb.com/2025/12/01/scylladb-vector-search-1b-benchmark/1OpenAI · Google2
scylladb.comhttps://scylladb.com/press-release/scylladb-brings-massive-scale-vector-search-to-real-time-ai/1OpenAI1
facebook.comhttps://facebook.com/scylladb/posts/billions-of-embeddings-zero-lag-scylladb-vector-search/1626845709442358/2Google1
scylladb.comhttps://scylladb.com/vector-search/2OpenAI1
firecrawl.devhttps://firecrawl.dev/blog/best-vector-databases3OpenAI · Google2
scylladb.comhttps://scylladb.com/3OpenAI1
medium.comhttps://medium.com/vespa/building-billion-scale-vector-search-part-one-4347ca57a8484Google1
scylladb.comhttps://scylladb.com/scale-real-time-ai/4OpenAI1
databricks.comhttps://databricks.com/blog/decoupled-design-billion-scale-vector-search5Google1
globenewswire.comhttps://globenewswire.com/news-release/2026/01/20/3221783/0/en/scylladb-brings-massive-scale-vector-search-to-real-time-ai.html5OpenAI1
blog.vectorchord.aihttps://blog.vectorchord.ai/scaling-vector-search-to-1-billion-on-postgresql6Google1
bigdataboutique.comhttps://bigdataboutique.com/blog/scaling-vector-search-performance-from-millions-to-billions-8d50a17Google1
p99conf.iohttps://p99conf.io/session/engineering-a-low-latency-vector-search-engine-for-scylladb/7OpenAI1
dl.acm.orghttps://dl.acm.org/doi/10.1145/37939268Google1
arxiv.orghttps://arxiv.org/html/2505.05885v29Google1
Snapshots
794067bc-f4fa-456f-8063-1db7efff0c35
Question set
vector-database-platforms-2026-07-27
Benchmark version
4-vector-database-platforms-2026-07-27-models-64232fd32583
What is kept
Measured in Vector DBs. Full answers are not stored or published, and no customer data is included.

See how often AI names you.

Enter your website. In about two minutes, Rank.ai asks ChatGPT, Claude and Gemini 12 questions your customers ask and grades how often they name you.

  • Your grade out of 100How often AI names you, cites your site, and how high it ranks you.
  • Who gets namedEvery competitor in the answers, most named first.
  • The pages AI readsThe sources behind each answer.
  • Three fixesWhat to fix first, with a brief for the first article.