How often does Google show an AI Overview for vector databases queries?

On 48.9% of the 223 queries measured in week 2026-W36, against 50.8% across the whole corpus.

Which domain does Google cite most for vector databases?

github.com, cited on 25 queries in this topic.

Vector databases — what Google shows, measured weekly

2026-W36

The shape of this topic

Queries measured

223

every week

AI Overview coverage

48.9%

corpus average 50.8%

Organic results

8.8

average per query

Weekly churn

14%

of the top 10 changes

Google answers vector databases queries itself less often than average — 48.9 against 50.8 percent across the corpus.

Citations

Who Google cites here

github.com 25

docs.python.org 19

en.wikipedia.org 19

lancedb.com 18

docs.typesense.com 18

qdrant.io 17

milvus.com 17

chroma.com 17

stackoverflow.com 17

typesense.com 15

opensearch.com 14

docs.milvus.com 14

Rankings

Who ranks here

github.com 74

pinecone.com 70

vectorize.io 69

stackoverflow.com 62

youtube.com 61

reddit.com 60

milvus.com 60

faiss.com 57

chroma.com 56

qdrant.io 54

typesense.com 53

weaviate.com 53

The gap

Cited more often than ranked

Domain	Citations	Gap
docs.python.org	19	+19
lancedb.com	18	+18
docs.typesense.com	18	+18
opensearch.com	14	+14
docs.milvus.com	14	+14
turbopuffer.com	13	+13
docs.qdrant.io	13	+13
developer.mozilla.org	13	+13

These domains earn a place in Google's own answer more often than they earn a place on page one. Whatever gets a source into an AI Overview, it is not only ranking.

Intent

By what the searcher wants

Intent	Queries	AI Overview
commercial	71	42.3%
informational	101	67.3%
comparison	28	35.7%
navigational	12	8.3%
support	11	0.0%

Intent is assigned when the query enters the corpus, not inferred afterwards, so this split is stable from week to week.

Blocks

Result features

AI Overview 48.9%

Queries in this topic

best vector databases vector databases comparison vector databases for beginners open source vector databases vector databases pricing comparison how does vector databases work Pinecone review Pinecone api Pinecone alternatives is Pinecone free Pinecone best practices what is Pinecone Pinecone rate limits Pinecone example how to use Pinecone Pinecone pricing Pinecone tutorial Pinecone not working Weaviate pricing Weaviate python Weaviate tutorial Weaviate review Weaviate best practices how to use Weaviate Weaviate alternatives Weaviate example Weaviate rate limits what is Weaviate Weaviate documentation is Weaviate free Qdrant api Qdrant alternatives Qdrant review Qdrant not working Qdrant rate limits Qdrant best practices Qdrant tutorial Qdrant pricing Qdrant python how to use Qdrant Qdrant documentation Milvus python Milvus best practices Milvus review Milvus alternatives Milvus documentation is Milvus free Milvus example how to use Milvus Milvus pricing Milvus not working Milvus rate limits what is Milvus Chroma review Chroma rate limits Chroma api Chroma best practices Chroma tutorial Chroma example Chroma alternatives is Chroma free how to use Chroma what is Chroma Chroma documentation Chroma pricing pgvector best practices pgvector tutorial pgvector explained pgvector example pgvector api what is pgvector best pgvector tools Redis Vector alternatives Redis Vector python Redis Vector rate limits Redis Vector tutorial is Redis Vector free Redis Vector pricing how to use Redis Vector Redis Vector best practices what is Redis Vector Redis Vector example Redis Vector review Redis Vector api Elasticsearch best practices Elasticsearch api Elasticsearch not working Elasticsearch tutorial Elasticsearch example Elasticsearch review Elasticsearch pricing Elasticsearch alternatives Elasticsearch python what is Elasticsearch is Elasticsearch free OpenSearch pricing OpenSearch api OpenSearch alternatives OpenSearch tutorial OpenSearch best practices is OpenSearch free OpenSearch example OpenSearch rate limits OpenSearch documentation OpenSearch python what is OpenSearch OpenSearch not working Vespa tutorial Vespa best practices Vespa review Vespa api what is Vespa how to use Vespa Vespa rate limits Vespa documentation Vespa not working Vespa example Vespa pricing is Vespa free LanceDB python LanceDB pricing LanceDB documentation LanceDB not working LanceDB alternatives LanceDB tutorial what is LanceDB how to use LanceDB LanceDB api LanceDB example LanceDB review LanceDB rate limits Turbopuffer python Turbopuffer pricing Turbopuffer review Turbopuffer example Turbopuffer alternatives Turbopuffer best practices Turbopuffer not working Turbopuffer rate limits Turbopuffer api is Turbopuffer free Turbopuffer documentation Vectorize best practices is Vectorize free Vectorize pricing Vectorize alternatives Vectorize python Vectorize tutorial Vectorize api Vectorize review how to use Vectorize Vectorize rate limits Vectorize documentation FAISS tutorial FAISS review FAISS pricing FAISS alternatives FAISS rate limits what is FAISS FAISS python FAISS example is FAISS free FAISS not working FAISS documentation FAISS best practices Typesense rate limits Typesense review how to use Typesense Typesense example Typesense tutorial Typesense documentation Typesense pricing Typesense best practices Typesense api what is Typesense is Typesense free Meilisearch python Meilisearch review how to use Meilisearch Meilisearch rate limits Meilisearch tutorial Meilisearch api Meilisearch documentation Meilisearch best practices Meilisearch pricing Meilisearch not working Meilisearch example what is Meilisearch Pinecone vs Weaviate Pinecone vs Milvus Weaviate vs Qdrant Weaviate vs Chroma Qdrant vs Milvus Qdrant vs pgvector Milvus vs Chroma Milvus vs Redis Vector Chroma vs pgvector Chroma vs Elasticsearch pgvector vs Redis Vector pgvector vs OpenSearch Redis Vector vs Elasticsearch Redis Vector vs Vespa Elasticsearch vs OpenSearch Elasticsearch vs LanceDB OpenSearch vs Vespa OpenSearch vs Turbopuffer Vespa vs LanceDB Vespa vs Vectorize LanceDB vs Turbopuffer LanceDB vs FAISS Turbopuffer vs Vectorize Turbopuffer vs Typesense Vectorize vs FAISS Vectorize vs Meilisearch FAISS vs Typesense Typesense vs Meilisearch

API

Measure a topic of your own

Pick your queries, run them on a schedule, keep what comes back. That is the whole method — the endpoint below returns the overview, its citations and the organic results together.

curl --request GET \
  --url 'https://serpens.p.rapidapi.com/api/v1/search_ai_overview?q=best%20vector%20databases&gl=us&hl=en&format=json' \
  --header 'x-rapidapi-host: serpens.p.rapidapi.com' \
  --header 'x-rapidapi-key: YOUR_KEY'

Start measuring

Free tier, no card. Same endpoint that produced every number on this page.

Get a free API key