Buyer prompt · published evidence

Which buying criteria matter most for production vector retrieval, including recall, latency, filtering, durability, and operations?

An exact prompt-level view of which reviewed brands surfaced and which public URLs the configured AI models cited. No answer text or tenant data is published.

Intent
commercial
Model providers
3
Categories
1
Last observed
Aug 4, 2026, 12:00 AM UTC
Competitive outcome

Brands surfaced

Ordered by provider breadth, then total mentions and owned-domain citations. A mention is not an endorsement or a position claim.

#BrandCategoryProvidersMentionsOwned citationsProvider evidence
01Qdrantqdrant.techVector DBs101Gemini
02Redisredis.ioVector DBs101Gemini
Model comparison

Answer matrix

One row per configured provider and category snapshot. Hashes prove answer identity without publishing stored answer text.

ProviderModel versionCategoryBrands surfacedCitationsUnique domainsAnswer hash
Openaiopenai/gpt-4o-miniVector DBsNone observed88866cf4dc…38bb1
Anthropicanthropic/claude-haiku-4-5Vector DBsNone observed00f272c0c9…2d837
Geminigoogle/gemini-2.5-flashVector DBsQdrant · Redis666d1fad5b…82ddd
URL-derived citations

Sources cited

Hostnames are derived from the returned public URLs. Best position is the smallest citation position observed.

Snapshot IDsb124696f-f8e4-4b21-8539-c7fd45268eeb
Corpus versionsvector-database-platforms-2026-07-27
Benchmark versions4-vector-database-platforms-2026-07-27-models-64232fd32583

Coverage: Vector DBs. Full answers stored: no · Full answers published: no · Tenant data included: no.