Subcategory · AI Citation Index
Vector Databases
Weaviate and Pinecone lead shortlists at 94%; Qdrant, Milvus tie evaluation at 84. Mongodb rising fast (+13 delta).
157 discovery queries · 486 head-to-heads · refreshed Jul 19, 2026
Discovery stage
The shortlist
Across 157 buyer-style "Vector Databases" queries
Weaviate (94.3% shortlist rate, 477 mentions) and Pinecone (93.6%, 512 mentions) dominate AI model recommendations across 157 prompts, both appearing in 4 models. Milvus follows at 91.7%, while Zilliz Cloud—its managed variant—trails at 80.3%. Traditional databases PostgreSQL and Mongodb crack the top 10 at 64.3% and 51.6% respectively, signaling extension into vector workloads.
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Signal by intent
By topic
Top 5 most-cited brands per intent cluster. Brands with zero citations in a topic are not shown.
Evaluation stage
Head-to-head
How often AI cites each brand across uniform category evaluation prompts · median 23/100
Qdrant, Milvus, and Weaviate share the top evaluation score of 84 across 48 head-to-head comparisons. Pinecone sits just behind at 82, while OpenSearch (81) and Elasticsearch (79) leverage existing search infrastructure. Zilliz Cloud scores 75 despite being Milvus's managed service; Mongodb lags at 67, the lowest among evaluated brands.
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Each brand's score is the share of category evaluation prompts where AI cited them across all four engines — the same prompt pool for every brand. Brands above the median citation rate have stronger presence in evaluation-stage queries.
Brands to know
In this category
Milvus
Open-source foundation scores 58 on unCited, ties for top evaluation at 84, and appears in 91.7% of shortlists. Zilliz Cloud's managed offering splits mentions but ranks lower on every metric.
Read brand profile →Pinecone
Leads total mentions (512) and nearly matches Weaviate's shortlist rate (93.6%). Evaluation score of 82 trails pure-play vector stores by 2 points, likely reflecting managed-service trade-offs.
Read brand profile →Qdrant
Ties Milvus and Weaviate at 84 in head-to-head evaluations but carries the lowest unCited score (17) among the top four shortlist leaders. Rust-based architecture differentiates from Python-heavy peers.
Read brand profile →Chroma
Developer-first positioning drives 64.3% shortlist rate and a score of 47—higher than Weaviate or Pinecone—but absent from evaluation data. Likely optimized for prototyping over production scale.
Read brand profile →Mongodb
Lowest evaluation score (67) yet rising fastest (+13 delta). Document database incumbency gives it 51.6% shortlist penetration as teams bolt vector search onto existing stacks rather than adopt purpose-built engines.
Read brand profile →Citation sources
Where AI pulls citations from
1000 citations captured across Vector Databases prompt runs.
Vendor pages
340Product, help, and marketing pages from tracked vendors
Independent sources
528Reviews, encyclopedias, forums, press — not vendor-owned
Buyer questions
What AI cites for top Vector Databases questions
Most-cited prompts across the buyer journey. Click any prompt to see the actual URLs AI engines link to.
Discovery
Buyers exploring the categoryEvaluation
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