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Rank.ai Index

Most cited pages in vector Databases answers

125 source pages ranked by how often AI answers cite them.
Recorded Sep 12, 2026Rotating scheduleSource: Rank.ai's prompt benchmark: fixed buying questions put to the OpenAI, Anthropic and Google model APIs, with Rank.ai's web searchHow this board is measuredCSV / JSON

11.1%

firecrawl.dev/blog/best-vector-databases ranks first

Cited answer coverage

125

Source pages ranked

of 128 tracked; the rest are below the quality bar

Sep 12

Snapshot recorded

2026 · Rotating schedule

36

Answers behind each row

From the OpenAI, Anthropic and Google model APIs

Follow changes

All 125 source pages by cited answer coverage

firecrawl.dev/blog/best-vector-databases leads at 11.1%; the middle of the board sits at 2.8%.

Ahead of second place
0%
Held by the top three
7%
Middle of the board
2.8%
Below half the leader
108 of 125
Highest 11.1%Middle 2.8%
1. firecrawl.dev/blog/best-vector-databases: 11.1%2. zenml.io/blog/vector-databases-for-rag: 11.1%3. milvus.io/: 8.3%4. redis.io/blog/best-open-source-vector-databases-comparison/: 8.3%5. qdrant.tech/: 8.3%6. youtube.com/watch: 8.3%7. feba-systeme.com/benchmarking-vector-dbs-recall-tail-latency-and-cost: 8.3%8. bigdataboutique.com/blog/scaling-vector-search-performance-from-millions-to-billions-8d50a1: 5.6%9. pinecone.io/learn/series/vector-databases-in-production-for-busy-engineers/vector-database-multi-tenancy/: 5.6%10. medium.com/@sparknp1/benchmarks-that-actually-pick-your-vector-db-f677a1412d51: 5.6%11. medium.com/@QuarkAndCode/improving-rag-with-reranking-and-hybrid-search-for-better-ai-retrieval-81eeb25131bb: 5.6%12. openmetal.io/resources/blog/when-self-hosting-vector-databases-becomes-cheaper-than-saas/: 5.6%13. scylladb.com/2025/12/01/scylladb-vector-search-1b-benchmark/: 5.6%14. weaviate.io/platform: 5.6%15. docs.aws.amazon.com/prescriptive-guidance/latest/choosing-an-aws-vector-database-for-rag-use-cases/vector-db-comparison.html: 5.6%16. docs.databricks.com/aws/en/ai-search/retrieval-quality: 5.6%17. medium.com/@pratik-rupareliya/top-15-vector-databases-in-2026-a-production-decision-guide-from-100-enterprise-deployments-dd58a04f51a5: 5.6%18. arxiv.org/html/2511.16654v2: 2.8%19. cognine.com/beyond-vector-search-why-hybrid-retrieval-is-becoming-the-enterprise-standard/: 2.8%20. couchbase.com/blog/vector-store-vs-vector-database-differences-and-similarities/: 2.8%21. creditforstartups.com/resources/pinecone-vs-qdrant: 2.8%22. docs.cloud.google.com/gemini-enterprise-agent-platform/models/embeddings/get-multimodal-embeddings: 2.8%23. gigaspaces.com/blog/best-vector-database-solutions-for-rag-applications: 2.8%24. linkedin.com/posts/prasad-k-18b038124_generativeai-artificialintelligence-rag-activity-7483204430985846784-TeYQ: 2.8%25. medium.com/@zilliz_learn/vdbbench-adds-cost-aware-benchmarking-for-vector-databases-42c4c9a6f799: 2.8%26. mehmetozkaya.medium.com/exploring-vector-databases-pinecone-chroma-weaviate-qdrant-milvus-pgvector-and-redis-f0618fe9e92d: 2.8%27. rank.ai/prompts/enterprise-vector-retrieval-private-networking: 2.8%28. rank.ai/prompts/serverless-vector-database-startup: 2.8%29. rank.ai/prompts/vector-database-buying-criteria: 2.8%30. rank.ai/prompts/vector-database-pricing-comparison: 2.8%31. redis.io/blog/best-vector-database/: 2.8%32. scylladb.com/press-release/scylladb-brings-massive-scale-vector-search-to-real-time-ai/: 2.8%33. zilliz.com/blog/zilliz-cloud-byoc-upgrades: 2.8%34. aboutvectordatabase.com/learn/the-recall-latency-trade-off-curve/: 2.8%35. actian.com/blog/databases/when-to-choose-on-premises-vs-cloud-for-vector-databases/: 2.8%36. aperturedata.io/blog/multimodal-data-intro-part1: 2.8%37. blog.sugiv.fyi/building-faster-multi-tenant-vector-search-curator: 2.8%38. ciopages.com/buyer-guides/vector-database: 2.8%39. cohere.com/blog/multimodal-embeddings: 2.8%40. community.pinecone.io/t/is-the-architecture-of-pinecone-multi-tenant/867: 2.8%41. facebook.com/scylladb/posts/billions-of-embeddings-zero-lag-scylladb-vector-search/1626845709442358/: 2.8%42. medium.com/mongodb/vector-databases-vs-traditional-databases-when-should-you-use-mongodb-c32c9aa67657: 2.8%43. petronellatech.com/blog/secure-rag-enterprise-architecture-patterns-for-accurate-leak-free-ai/: 2.8%44. rank.ai/entities/vector-database-platforms-prompt-vector-database-buying-criteria: 2.8%45. reddit.com/r/Rag/comments/1mqp4qs/best_vector_db_for_production_ready_rag/: 2.8%46. scylladb.com/vector-search/: 2.8%47. strapi.io/blog/best-vector-databases-ai-applications: 2.8%48. vastdata.com/blog/architecture-behind-our-11x-vector-benchmark: 2.8%49. webbycrown.com/hybrid-search-for-rag/: 2.8%50. xenoss.io/blog/vector-database-comparison-pinecone-qdrant-weaviate: 2.8%51. actian.com/blog/databases/how-to-evaluate-vector-databases-in-2026/: 2.8%52. alphacorp.ai/blog/best-vector-databases-for-rag-2026-top-7-picks: 2.8%53. aws.amazon.com/blogs/machine-learning/scale-creative-asset-discovery-with-amazon-nova-multimodal-embeddings-unified-vector-search/: 2.8%54. benchant.com/blog/single-store-vector-vs-pinecone-zilliz-2025: 2.8%55. cloud.google.com/discover/what-is-a-vector-database: 2.8%56. encore.dev/articles/best-vector-databases: 2.8%57. engineersguide.substack.com/p/best-vector-databases-rag: 2.8%58. iternal.ai/insights/best-vector-databases-2026: 2.8%59. learn.microsoft.com/en-us/azure/foundry/agents/how-to/virtual-networks: 2.8%60. linkedin.com/posts/ashish-jangra_47metadatafilteringinragashishjangra-activity-7497503001109209088-k2PK: 2.8%61. medium.com/data-science-collective/pinecone-vs-weaviate-vs-qdrant-vs-milvus-66d5bfbcc460: 2.8%62. mlops.community/blog/how-multimodal-vector-databases-are-transforming-challenges-across-industries: 2.8%63. npblue.com/ai/rag/multi-tenant-vector-stores/: 2.8%64. reddit.com/r/vectordatabase/comments/1csz7l8/multitenancy_for_vectordbs/: 2.8%65. redis.io/blog/common-challenges-working-with-vector-databases/: 2.8%66. scylladb.com/: 2.8%67. sec.cloudapps.cisco.com/security/center/resources/securing-vector-databases: 2.8%68. zilliz.com/blog/vdbbench-adds-cost-aware-benchmarking-for-vector-databases: 2.8%69. arxiv.org/html/2310.11703v2: 2.8%70. arxiv.org/html/2510.24402v1: 2.8%71. aws.amazon.com/blogs/apn/reimagining-vector-databases-for-the-generative-ai-era-with-pinecone-serverless-on-aws/: 2.8%72. blckalpaca.at/en/knowledge-base/ai-agents/what-is-a-rag-system/pinecone-vs-weaviate-vs-qdrant: 2.8%73. cloudsecurityalliance.org/artifacts/using-zero-trust-to-secure-enterprise-information-in-llm-environments: 2.8%74. digeniotech.com/ai-resource/vector-db/multi-tenancy-vector-databases-isolating-data-at-scale.php: 2.8%75. instaclustr.com/education/vector-database/top-10-open-source-vector-databases/: 2.8%76. medium.com/@tenyks_blogger/multi-modal-image-search-with-embeddings-vector-dbs-cee61c70a88a: 2.8%77. medium.com/vespa/building-billion-scale-vector-search-part-one-4347ca57a848: 2.8%78. pecollective.com/tools/best-vector-databases/: 2.8%79. pinecone.io/learn/vector-database/: 2.8%80. pub.towardsai.net/vector-database-for-rag-the-top-10-to-know-in-2026-a7ddae9bf893: 2.8%81. scylladb.com/scale-real-time-ai/: 2.8%82. stackoverflow.blog/2023/09/20/do-you-need-a-specialized-vector-database-to-implement-vector-search-well/: 2.8%83. superlinked.com/blog/choosing-a-vector-database: 2.8%84. velodb.io/glossary/pinecone-vector-database: 2.8%85. weaviate.io/blog/multimodal-guide: 2.8%86. aiamastery.substack.com/p/lesson-23-hybrid-search-and-filtering: 2.8%87. community.pinecone.io/t/is-the-architecture-of-pinecone-multi-tenant/867/2: 2.8%88. databricks.com/blog/decoupled-design-billion-scale-vector-search: 2.8%89. dev.to/actiandev/whats-changing-in-vector-databases-in-2026-3pbo: 2.8%90. dev.to/aws-builders/aws-vector-databases-part-3-choosing-the-right-vector-database-on-aws-375m: 2.8%91. digitalapplied.com/blog/vector-databases-for-ai-agents-pinecone-qdrant-2026: 2.8%92. facebook.com/groups/chiefai/posts/3117293691797245/: 2.8%93. globenewswire.com/news-release/2026/01/20/3221783/0/en/scylladb-brings-massive-scale-vector-search-to-real-time-ai.html: 2.8%94. kalviumlabs.ai/blog/vector-databases-compared-pgvector-pinecone-qdrant-weaviate/: 2.8%95. liveblocks.io/blog/whats-the-best-vector-database-for-building-ai-products: 2.8%96. medium.com/@ThinkingLoop/5-ironclad-rules-for-multi-tenant-vector-isolation-41d8ec2c3a20: 2.8%97. milvus.io/blog/choosing-the-right-vector-database-for-your-ai-apps.md: 2.8%98. milvus.io/blog/how-to-filter-efficiently-without-killing-recall.md: 2.8%99. milvus.io/blog/multimodal-semantic-search-with-images-and-text.md: 2.8%100. redis.io/blog/vector-database-alternatives-rag-pipelines/: 2.8%101. tigergraph.com/glossary/multimodal-embeddings/: 2.8%102. aipmguru.substack.com/p/vector-database-101-what-every-ai: 2.8%103. blog.vectorchord.ai/scaling-vector-search-to-1-billion-on-postgresql: 2.8%104. databricks.com/blog/serverless-database: 2.8%105. dev.to/krunalkanojiya/pinecone-vs-weaviate-vs-milvus-vs-qdrant-which-vector-db-in-2026-26dc: 2.8%106. elastic.co/search-labs/blog/multimodal-embeddings-ecommerce-product-search: 2.8%107. medium.com/@soumitsr/a-broke-b-chs-guide-to-tech-start-up-choosing-vector-database-part-1-local-self-hosted-4ebe4eec3045: 2.8%108. mongodb.com/community/forums/t/atlas-vector-search-performance-guide-benchmarks/326613: 2.8%109. pingcap.com/compare/best-vector-database/: 2.8%110. rconfig.com/products/vector: 2.8%111. reddit.com/r/vectordatabase/comments/1kwaqx1/i_benchmarked_qdrant_vs_milvus_vs_weaviate_vs/: 2.8%112. runtime.news/pinecones-new-serverless-architecture-hopes-to-make-the-vector-database-more-versatile/: 2.8%113. tigerdata.com/blog/how-to-choose-a-vector-database: 2.8%114. arxiv.org/html/2401.07119v1: 2.8%115. arxiv.org/html/2507.00379v1: 2.8%116. docs.cloud.google.com/architecture/private-connectivity-rag-capable-gen-ai: 2.8%117. p99conf.io/session/engineering-a-low-latency-vector-search-engine-for-scylladb/: 2.8%118. reddit.com/r/LangChain/comments/170jigz/my_strategy_for_picking_a_vector_database_a/: 2.8%119. reddit.com/r/Rag/comments/1r3y4ys/which_vector_database_do_we_like_for/: 2.8%120. reddit.com/r/vectordatabase/comments/1mo6sxq/why_most_serverless_vector_databases_are_slow_and/: 2.8%121. soeasie.com/blog/considerations-for-optimizing-media-retrieval-systems-using-multimodal-embeddings: 2.8%122. dl.acm.org/doi/10.1145/3793926: 2.8%123. ksofttechnologies.com/blogs/how-rag-works-inside-a-closed-enterprise-environment: 2.8%124. reddit.com/r/vectordatabase/comments/1l7nppj/do_you_use_any_opensource_vector_database_how/: 2.8%125. arxiv.org/html/2505.05885v2: 2.8%
Rank 1One bar per published rowRank 125

The prompt boards are re-run in rotation, about one category a day, so each board refreshes every few weeks and shows the date of its snapshot.

page cited answer: 1 on 108 of 125 rows · page engine breadth: 1 on 109 of 125 rows · 36 checks behind each row.

Most cited pages in vector Databases answers current rankings
RankNameCited answer coveragePage best positionPage mean positionChangeWhy
01firecrawl.dev/blog/best-vector-databases11.1%13.5 1This rank
02zenml.io/blog/vector-databases-for-rag11.1%23.5 1This rank
03milvus.io/8.3%22 63Showing
04redis.io/blog/best-open-source-vector-databases-comparison/8.3%34.3 3This rank
05qdrant.tech/8.3%13.7 1This rank
06youtube.com/watch8.3%45.3 3This rank
07feba-systeme.com/benchmarking-vector-dbs-recall-tail-latency-and-cost8.3%12.3 39This rank
08bigdataboutique.com/blog/scaling-vector-search-performance-from-millions-to-billions-8d50a15.6%45.5—This rank
09pinecone.io/learn/series/vector-databases-in-production-for-busy-engineers/vector-database-multi-tenancy/5.6%11 24This rank
10medium.com/@sparknp1/benchmarks-that-actually-pick-your-vector-db-f677a1412d515.6%11.5—This rank
11medium.com/@QuarkAndCode/improving-rag-with-reranking-and-hybrid-search-for-better-ai-retrieval-81eeb25131bb5.6%23—This rank
12openmetal.io/resources/blog/when-self-hosting-vector-databases-becomes-cheaper-than-saas/5.6%13 6This rank
13scylladb.com/2025/12/01/scylladb-vector-search-1b-benchmark/5.6%13.5 24This rank
14weaviate.io/platform5.6%33.5—This rank
15docs.aws.amazon.com/prescriptive-guidance/latest/choosing-an-aws-vector-database-for-rag-use-cases/vector-db-comparison.html5.6%24 11This rank
16docs.databricks.com/aws/en/ai-search/retrieval-quality5.6%34 11This rank
17medium.com/@pratik-rupareliya/top-15-vector-databases-in-2026-a-production-decision-guide-from-100-enterprise-deployments-dd58a04f51a55.6%33.5—This rank
18arxiv.org/html/2511.16654v22.8%11—This rank
19cognine.com/beyond-vector-search-why-hybrid-retrieval-is-becoming-the-enterprise-standard/2.8%11—This rank
20couchbase.com/blog/vector-store-vs-vector-database-differences-and-similarities/2.8%11 40This rank
21creditforstartups.com/resources/pinecone-vs-qdrant2.8%11—This rank
22docs.cloud.google.com/gemini-enterprise-agent-platform/models/embeddings/get-multimodal-embeddings2.8%11 68This rank
23gigaspaces.com/blog/best-vector-database-solutions-for-rag-applications2.8%11 5This rank
24linkedin.com/posts/prasad-k-18b038124_generativeai-artificialintelligence-rag-activity-7483204430985846784-TeYQ2.8%11—This rank
25medium.com/@zilliz_learn/vdbbench-adds-cost-aware-benchmarking-for-vector-databases-42c4c9a6f7992.8%11 83This rank
26mehmetozkaya.medium.com/exploring-vector-databases-pinecone-chroma-weaviate-qdrant-milvus-pgvector-and-redis-f0618fe9e92d2.8%11 5This rank
27rank.ai/prompts/enterprise-vector-retrieval-private-networking2.8%11—This rank
28rank.ai/prompts/serverless-vector-database-startup2.8%11—This rank
29rank.ai/prompts/vector-database-buying-criteria2.8%11—This rank
30rank.ai/prompts/vector-database-pricing-comparison2.8%11—This rank
31redis.io/blog/best-vector-database/2.8%11 18This rank
32scylladb.com/press-release/scylladb-brings-massive-scale-vector-search-to-real-time-ai/2.8%11—This rank
33zilliz.com/blog/zilliz-cloud-byoc-upgrades2.8%11—This rank
34aboutvectordatabase.com/learn/the-recall-latency-trade-off-curve/2.8%22—This rank
35actian.com/blog/databases/when-to-choose-on-premises-vs-cloud-for-vector-databases/2.8%22 22This rank
36aperturedata.io/blog/multimodal-data-intro-part12.8%22—This rank
37blog.sugiv.fyi/building-faster-multi-tenant-vector-search-curator2.8%22—This rank
38ciopages.com/buyer-guides/vector-database2.8%22—This rank
39cohere.com/blog/multimodal-embeddings2.8%22 34This rank
40community.pinecone.io/t/is-the-architecture-of-pinecone-multi-tenant/8672.8%22—This rank
41facebook.com/scylladb/posts/billions-of-embeddings-zero-lag-scylladb-vector-search/1626845709442358/2.8%22—This rank
42medium.com/mongodb/vector-databases-vs-traditional-databases-when-should-you-use-mongodb-c32c9aa676572.8%22 50This rank
43petronellatech.com/blog/secure-rag-enterprise-architecture-patterns-for-accurate-leak-free-ai/2.8%22—This rank
44rank.ai/entities/vector-database-platforms-prompt-vector-database-buying-criteria2.8%22—This rank
45reddit.com/r/Rag/comments/1mqp4qs/best_vector_db_for_production_ready_rag/2.8%22—This rank
46scylladb.com/vector-search/2.8%22—This rank
47strapi.io/blog/best-vector-databases-ai-applications2.8%22—This rank
48vastdata.com/blog/architecture-behind-our-11x-vector-benchmark2.8%22—This rank
49webbycrown.com/hybrid-search-for-rag/2.8%22 8This rank
50xenoss.io/blog/vector-database-comparison-pinecone-qdrant-weaviate2.8%22 6This rank
51actian.com/blog/databases/how-to-evaluate-vector-databases-in-2026/2.8%33—This rank
52alphacorp.ai/blog/best-vector-databases-for-rag-2026-top-7-picks2.8%33—This rank
53aws.amazon.com/blogs/machine-learning/scale-creative-asset-discovery-with-amazon-nova-multimodal-embeddings-unified-vector-search/2.8%33 5This rank
54benchant.com/blog/single-store-vector-vs-pinecone-zilliz-20252.8%33—This rank
55cloud.google.com/discover/what-is-a-vector-database2.8%33—This rank
56encore.dev/articles/best-vector-databases2.8%33—This rank
57engineersguide.substack.com/p/best-vector-databases-rag2.8%33—This rank
58iternal.ai/insights/best-vector-databases-20262.8%33 5This rank
59learn.microsoft.com/en-us/azure/foundry/agents/how-to/virtual-networks2.8%33—This rank
60linkedin.com/posts/ashish-jangra_47metadatafilteringinragashishjangra-activity-7497503001109209088-k2PK2.8%33—This rank
61medium.com/data-science-collective/pinecone-vs-weaviate-vs-qdrant-vs-milvus-66d5bfbcc4602.8%33—This rank
62mlops.community/blog/how-multimodal-vector-databases-are-transforming-challenges-across-industries2.8%33—This rank
63npblue.com/ai/rag/multi-tenant-vector-stores/2.8%33—This rank
64reddit.com/r/vectordatabase/comments/1csz7l8/multitenancy_for_vectordbs/2.8%33—This rank
65redis.io/blog/common-challenges-working-with-vector-databases/2.8%33—This rank
66scylladb.com/2.8%33—This rank
67sec.cloudapps.cisco.com/security/center/resources/securing-vector-databases2.8%33 54This rank
68zilliz.com/blog/vdbbench-adds-cost-aware-benchmarking-for-vector-databases2.8%33—This rank
69arxiv.org/html/2310.11703v22.8%44—This rank
70arxiv.org/html/2510.24402v12.8%44 53This rank
71aws.amazon.com/blogs/apn/reimagining-vector-databases-for-the-generative-ai-era-with-pinecone-serverless-on-aws/2.8%44—This rank
72blckalpaca.at/en/knowledge-base/ai-agents/what-is-a-rag-system/pinecone-vs-weaviate-vs-qdrant2.8%44—This rank
73cloudsecurityalliance.org/artifacts/using-zero-trust-to-secure-enterprise-information-in-llm-environments2.8%44 54This rank
74digeniotech.com/ai-resource/vector-db/multi-tenancy-vector-databases-isolating-data-at-scale.php2.8%44 2This rank
75instaclustr.com/education/vector-database/top-10-open-source-vector-databases/2.8%44 59This rank
76medium.com/@tenyks_blogger/multi-modal-image-search-with-embeddings-vector-dbs-cee61c70a88a2.8%44 52This rank
77medium.com/vespa/building-billion-scale-vector-search-part-one-4347ca57a8482.8%44—This rank
78pecollective.com/tools/best-vector-databases/2.8%44—This rank
79pinecone.io/learn/vector-database/2.8%44—This rank
80pub.towardsai.net/vector-database-for-rag-the-top-10-to-know-in-2026-a7ddae9bf8932.8%44—This rank
81scylladb.com/scale-real-time-ai/2.8%44—This rank
82stackoverflow.blog/2023/09/20/do-you-need-a-specialized-vector-database-to-implement-vector-search-well/2.8%44—This rank
83superlinked.com/blog/choosing-a-vector-database2.8%44—This rank
84velodb.io/glossary/pinecone-vector-database2.8%44 45This rank
85weaviate.io/blog/multimodal-guide2.8%44 45This rank
86aiamastery.substack.com/p/lesson-23-hybrid-search-and-filtering2.8%55—This rank
87community.pinecone.io/t/is-the-architecture-of-pinecone-multi-tenant/867/22.8%55—This rank
88databricks.com/blog/decoupled-design-billion-scale-vector-search2.8%55 1This rank
89dev.to/actiandev/whats-changing-in-vector-databases-in-2026-3pbo2.8%55—This rank
90dev.to/aws-builders/aws-vector-databases-part-3-choosing-the-right-vector-database-on-aws-375m2.8%55 76This rank
91digitalapplied.com/blog/vector-databases-for-ai-agents-pinecone-qdrant-20262.8%55 30This rank
92facebook.com/groups/chiefai/posts/3117293691797245/2.8%55—This rank
93globenewswire.com/news-release/2026/01/20/3221783/0/en/scylladb-brings-massive-scale-vector-search-to-real-time-ai.html2.8%55—This rank
94kalviumlabs.ai/blog/vector-databases-compared-pgvector-pinecone-qdrant-weaviate/2.8%55—This rank
95liveblocks.io/blog/whats-the-best-vector-database-for-building-ai-products2.8%55 86This rank
96medium.com/@ThinkingLoop/5-ironclad-rules-for-multi-tenant-vector-isolation-41d8ec2c3a202.8%55—This rank
97milvus.io/blog/choosing-the-right-vector-database-for-your-ai-apps.md2.8%55—This rank
98milvus.io/blog/how-to-filter-efficiently-without-killing-recall.md2.8%55—This rank
99milvus.io/blog/multimodal-semantic-search-with-images-and-text.md2.8%55—This rank
100redis.io/blog/vector-database-alternatives-rag-pipelines/2.8%55—This rank
101tigergraph.com/glossary/multimodal-embeddings/2.8%55 15This rank
102aipmguru.substack.com/p/vector-database-101-what-every-ai2.8%66—This rank
103blog.vectorchord.ai/scaling-vector-search-to-1-billion-on-postgresql2.8%66 23This rank
104databricks.com/blog/serverless-database2.8%66—This rank
105dev.to/krunalkanojiya/pinecone-vs-weaviate-vs-milvus-vs-qdrant-which-vector-db-in-2026-26dc2.8%66—This rank
106elastic.co/search-labs/blog/multimodal-embeddings-ecommerce-product-search2.8%66—This rank
107medium.com/@soumitsr/a-broke-b-chs-guide-to-tech-start-up-choosing-vector-database-part-1-local-self-hosted-4ebe4eec30452.8%66 78This rank
108mongodb.com/community/forums/t/atlas-vector-search-performance-guide-benchmarks/3266132.8%66—This rank
109pingcap.com/compare/best-vector-database/2.8%66 87This rank
110rconfig.com/products/vector2.8%66—This rank
111reddit.com/r/vectordatabase/comments/1kwaqx1/i_benchmarked_qdrant_vs_milvus_vs_weaviate_vs/2.8%66—This rank
112runtime.news/pinecones-new-serverless-architecture-hopes-to-make-the-vector-database-more-versatile/2.8%66—This rank
113tigerdata.com/blog/how-to-choose-a-vector-database2.8%66 60This rank
114arxiv.org/html/2401.07119v12.8%77—This rank
115arxiv.org/html/2507.00379v12.8%77—This rank
116docs.cloud.google.com/architecture/private-connectivity-rag-capable-gen-ai2.8%77 39This rank
117p99conf.io/session/engineering-a-low-latency-vector-search-engine-for-scylladb/2.8%77—This rank
118reddit.com/r/LangChain/comments/170jigz/my_strategy_for_picking_a_vector_database_a/2.8%77 113This rank
119reddit.com/r/Rag/comments/1r3y4ys/which_vector_database_do_we_like_for/2.8%77 5This rank
120reddit.com/r/vectordatabase/comments/1mo6sxq/why_most_serverless_vector_databases_are_slow_and/2.8%77—This rank
121soeasie.com/blog/considerations-for-optimizing-media-retrieval-systems-using-multimodal-embeddings2.8%77—This rank
122dl.acm.org/doi/10.1145/37939262.8%88—This rank
123ksofttechnologies.com/blogs/how-rag-works-inside-a-closed-enterprise-environment2.8%88—This rank
124reddit.com/r/vectordatabase/comments/1l7nppj/do_you_use_any_opensource_vector_database_how/2.8%88—This rank
125arxiv.org/html/2505.05885v22.8%99—This rank

Why this rank

milvus.io/ on Most-cited pages in Vector Databases answers

Snapshot of Sep 12, 2026, 12:00 AM UTC · Link to this snapshot

Some explanation inputs are unavailable. Not published: the evidence frozen with this snapshot.

Ranks privacy-safe canonical citation pages in the complete public prompt benchmark without additional provider calls.

3

Rank on this board

8.333 percent

Score

36

Answers behind the score

100% confidence · 1 of 1 components evidenced

What the score is built from

1 of 1 evidenced

Every component evidenced · 1 evidence record each

Components of milvus.io/'s score
ComponentValueContribution
Page answer coverage8.3333338.333

Moved up since the previous snapshot

+63 places
  1. Page answer coverage2.778 to 8.333
    +5.556
  2. Position numerator3 to 6
    +3
  3. Position denominator1 to 3
    +2
  4. Page cited answer1 to 3
    +2
  5. Page engine breadth1 to 3
    +2
  6. Page best position3 to 2
    -1
  7. Page mean position3 to 2
    -1
  8. Page median position3 to 2
    -1
  9. Answer denominator36 to 36
    0
  10. Engine denominator3 to 3
    0
  11. Prompt denominator12 to 12
    0
  12. Page prompt breadth1 to 1
    0

Where each number comes from

7 public records
  • Cited-answer coveragePage answer coverage · observed Sep 12, 2026, 12:00 AM UTC8.333 percent100% confidence
    Source
    Rank.ai Vector Databases Prompt Benchmark
    Grade
    A
    Freshness
    fresh
    Locator
    {"corpusVersion":"vector-database-platforms-2026-07-27","runArtifactIds":["e33dd985-f176-4ab4-9454-aee96d33c088","dcbac240-1491-4352-842c-0806750555ae","0d37b2a2-eb3a-439a-a79f-41e84711c1a4","bf953d93-d4cf-4f60-a020-6d347d999323","071dbba4-9632-433a-b537-174e3f51b2de","ba80dea3-391d-4437-9459-e60a9d2ea270","9124e2fb-1ff5-4d4e-a5a4-f73819f680a0","0bc1d0cf-6fe6-4ac9-84ec-c865babfcab8","d5047f79-2f05-40f8-86a9-6cb4a813ed07","cef04144-25c1-44e7-ad6e-7f5f564b05ef","3585da81-4f5f-492f-9da3-a3fbf759d91d","1c6b58cf-7892-4808-93ae-6dbb60ecc298","b783808a-2cf8-431f-9345-d4b420ff2cec","08d3b7f5-a9d2-4e9e-9c5c-f6556f5ddbb8","f705d98a-5806-4721-a721-a502ef397f5c","0b1394c3-a8ca-47b3-a187-684d6a145034","3c9d31d8-537e-40f2-b7f2-216c0859da16","080de0fb-96ee-44d0-96a5-51bc5ee55213","54094093-8713-40cf-a8b0-49631e8d91a6","7b904caf-c982-47d4-8de3-1d1ccd86b56e","8e5d85b5-7830-4473-8e40-c607c13b54ba","2047a3bb-e040-4b7b-82b6-bde729dd621a","8588f880-47ff-4daf-8bc6-f38d0d042e19","5c0d184c-90d6-4362-a70f-146080a509e7","4ae3f702-03fe-4114-bf19-3e004b674d38","38d5e84f-c1cd-4974-8d4d-7a0f20cfb88d","2f773a7d-d6f0-4f03-ace9-469ec5ced46d","a8d43bb0-c5f0-45a3-956f-a653df389bdc","9e4ec911-0582-44fe-9676-7a41f7739e01","0e2afed9-0e73-47fa-b652-54438e0c6550","e61d72df-b2a3-4fcb-b5b9-74f69aebac68","f34c5a15-9290-4144-9dcd-f5100777220c","8502a803-448b-41df-8089-513d17573c3e","1469281a-da62-4e78-8a6d-ed5d882547cf","bae7de20-12db-4bb0-80ec-91c424506360","97ece4d4-251c-4d3a-9366-6e5fe4bd799c"],"benchmarkVersion":"4-vector-database-platforms-2026-07-27-models-64232fd32583","providerMatrixVersion":"64232fd32583"}
    Open the source
  • Best citation positionPage best position · observed Sep 12, 2026, 12:00 AM UTC2 position100% confidence
    Source
    Rank.ai Vector Databases Prompt Benchmark
    Grade
    A
    Freshness
    fresh
    Locator
    {"corpusVersion":"vector-database-platforms-2026-07-27","runArtifactIds":["e33dd985-f176-4ab4-9454-aee96d33c088","dcbac240-1491-4352-842c-0806750555ae","0d37b2a2-eb3a-439a-a79f-41e84711c1a4","bf953d93-d4cf-4f60-a020-6d347d999323","071dbba4-9632-433a-b537-174e3f51b2de","ba80dea3-391d-4437-9459-e60a9d2ea270","9124e2fb-1ff5-4d4e-a5a4-f73819f680a0","0bc1d0cf-6fe6-4ac9-84ec-c865babfcab8","d5047f79-2f05-40f8-86a9-6cb4a813ed07","cef04144-25c1-44e7-ad6e-7f5f564b05ef","3585da81-4f5f-492f-9da3-a3fbf759d91d","1c6b58cf-7892-4808-93ae-6dbb60ecc298","b783808a-2cf8-431f-9345-d4b420ff2cec","08d3b7f5-a9d2-4e9e-9c5c-f6556f5ddbb8","f705d98a-5806-4721-a721-a502ef397f5c","0b1394c3-a8ca-47b3-a187-684d6a145034","3c9d31d8-537e-40f2-b7f2-216c0859da16","080de0fb-96ee-44d0-96a5-51bc5ee55213","54094093-8713-40cf-a8b0-49631e8d91a6","7b904caf-c982-47d4-8de3-1d1ccd86b56e","8e5d85b5-7830-4473-8e40-c607c13b54ba","2047a3bb-e040-4b7b-82b6-bde729dd621a","8588f880-47ff-4daf-8bc6-f38d0d042e19","5c0d184c-90d6-4362-a70f-146080a509e7","4ae3f702-03fe-4114-bf19-3e004b674d38","38d5e84f-c1cd-4974-8d4d-7a0f20cfb88d","2f773a7d-d6f0-4f03-ace9-469ec5ced46d","a8d43bb0-c5f0-45a3-956f-a653df389bdc","9e4ec911-0582-44fe-9676-7a41f7739e01","0e2afed9-0e73-47fa-b652-54438e0c6550","e61d72df-b2a3-4fcb-b5b9-74f69aebac68","f34c5a15-9290-4144-9dcd-f5100777220c","8502a803-448b-41df-8089-513d17573c3e","1469281a-da62-4e78-8a6d-ed5d882547cf","bae7de20-12db-4bb0-80ec-91c424506360","97ece4d4-251c-4d3a-9366-6e5fe4bd799c"],"benchmarkVersion":"4-vector-database-platforms-2026-07-27-models-64232fd32583","providerMatrixVersion":"64232fd32583"}
    Open the source
  • Cited answersPage cited answer · observed Sep 12, 2026, 12:00 AM UTC3 answers100% confidence
    Source
    Rank.ai Vector Databases Prompt Benchmark
    Grade
    A
    Freshness
    fresh
    Locator
    {"corpusVersion":"vector-database-platforms-2026-07-27","runArtifactIds":["e33dd985-f176-4ab4-9454-aee96d33c088","dcbac240-1491-4352-842c-0806750555ae","0d37b2a2-eb3a-439a-a79f-41e84711c1a4","bf953d93-d4cf-4f60-a020-6d347d999323","071dbba4-9632-433a-b537-174e3f51b2de","ba80dea3-391d-4437-9459-e60a9d2ea270","9124e2fb-1ff5-4d4e-a5a4-f73819f680a0","0bc1d0cf-6fe6-4ac9-84ec-c865babfcab8","d5047f79-2f05-40f8-86a9-6cb4a813ed07","cef04144-25c1-44e7-ad6e-7f5f564b05ef","3585da81-4f5f-492f-9da3-a3fbf759d91d","1c6b58cf-7892-4808-93ae-6dbb60ecc298","b783808a-2cf8-431f-9345-d4b420ff2cec","08d3b7f5-a9d2-4e9e-9c5c-f6556f5ddbb8","f705d98a-5806-4721-a721-a502ef397f5c","0b1394c3-a8ca-47b3-a187-684d6a145034","3c9d31d8-537e-40f2-b7f2-216c0859da16","080de0fb-96ee-44d0-96a5-51bc5ee55213","54094093-8713-40cf-a8b0-49631e8d91a6","7b904caf-c982-47d4-8de3-1d1ccd86b56e","8e5d85b5-7830-4473-8e40-c607c13b54ba","2047a3bb-e040-4b7b-82b6-bde729dd621a","8588f880-47ff-4daf-8bc6-f38d0d042e19","5c0d184c-90d6-4362-a70f-146080a509e7","4ae3f702-03fe-4114-bf19-3e004b674d38","38d5e84f-c1cd-4974-8d4d-7a0f20cfb88d","2f773a7d-d6f0-4f03-ace9-469ec5ced46d","a8d43bb0-c5f0-45a3-956f-a653df389bdc","9e4ec911-0582-44fe-9676-7a41f7739e01","0e2afed9-0e73-47fa-b652-54438e0c6550","e61d72df-b2a3-4fcb-b5b9-74f69aebac68","f34c5a15-9290-4144-9dcd-f5100777220c","8502a803-448b-41df-8089-513d17573c3e","1469281a-da62-4e78-8a6d-ed5d882547cf","bae7de20-12db-4bb0-80ec-91c424506360","97ece4d4-251c-4d3a-9366-6e5fe4bd799c"],"benchmarkVersion":"4-vector-database-platforms-2026-07-27-models-64232fd32583","providerMatrixVersion":"64232fd32583"}
    Open the source
  • Engine breadthPage engine breadth · observed Sep 12, 2026, 12:00 AM UTC3 engines100% confidence
    Source
    Rank.ai Vector Databases Prompt Benchmark
    Grade
    A
    Freshness
    fresh
    Locator
    {"corpusVersion":"vector-database-platforms-2026-07-27","runArtifactIds":["e33dd985-f176-4ab4-9454-aee96d33c088","dcbac240-1491-4352-842c-0806750555ae","0d37b2a2-eb3a-439a-a79f-41e84711c1a4","bf953d93-d4cf-4f60-a020-6d347d999323","071dbba4-9632-433a-b537-174e3f51b2de","ba80dea3-391d-4437-9459-e60a9d2ea270","9124e2fb-1ff5-4d4e-a5a4-f73819f680a0","0bc1d0cf-6fe6-4ac9-84ec-c865babfcab8","d5047f79-2f05-40f8-86a9-6cb4a813ed07","cef04144-25c1-44e7-ad6e-7f5f564b05ef","3585da81-4f5f-492f-9da3-a3fbf759d91d","1c6b58cf-7892-4808-93ae-6dbb60ecc298","b783808a-2cf8-431f-9345-d4b420ff2cec","08d3b7f5-a9d2-4e9e-9c5c-f6556f5ddbb8","f705d98a-5806-4721-a721-a502ef397f5c","0b1394c3-a8ca-47b3-a187-684d6a145034","3c9d31d8-537e-40f2-b7f2-216c0859da16","080de0fb-96ee-44d0-96a5-51bc5ee55213","54094093-8713-40cf-a8b0-49631e8d91a6","7b904caf-c982-47d4-8de3-1d1ccd86b56e","8e5d85b5-7830-4473-8e40-c607c13b54ba","2047a3bb-e040-4b7b-82b6-bde729dd621a","8588f880-47ff-4daf-8bc6-f38d0d042e19","5c0d184c-90d6-4362-a70f-146080a509e7","4ae3f702-03fe-4114-bf19-3e004b674d38","38d5e84f-c1cd-4974-8d4d-7a0f20cfb88d","2f773a7d-d6f0-4f03-ace9-469ec5ced46d","a8d43bb0-c5f0-45a3-956f-a653df389bdc","9e4ec911-0582-44fe-9676-7a41f7739e01","0e2afed9-0e73-47fa-b652-54438e0c6550","e61d72df-b2a3-4fcb-b5b9-74f69aebac68","f34c5a15-9290-4144-9dcd-f5100777220c","8502a803-448b-41df-8089-513d17573c3e","1469281a-da62-4e78-8a6d-ed5d882547cf","bae7de20-12db-4bb0-80ec-91c424506360","97ece4d4-251c-4d3a-9366-6e5fe4bd799c"],"benchmarkVersion":"4-vector-database-platforms-2026-07-27-models-64232fd32583","providerMatrixVersion":"64232fd32583"}
    Open the source
  • Mean citation positionPage mean position · observed Sep 12, 2026, 12:00 AM UTC2 position100% confidence
    Source
    Rank.ai Vector Databases Prompt Benchmark
    Grade
    A
    Freshness
    fresh
    Locator
    {"corpusVersion":"vector-database-platforms-2026-07-27","runArtifactIds":["e33dd985-f176-4ab4-9454-aee96d33c088","dcbac240-1491-4352-842c-0806750555ae","0d37b2a2-eb3a-439a-a79f-41e84711c1a4","bf953d93-d4cf-4f60-a020-6d347d999323","071dbba4-9632-433a-b537-174e3f51b2de","ba80dea3-391d-4437-9459-e60a9d2ea270","9124e2fb-1ff5-4d4e-a5a4-f73819f680a0","0bc1d0cf-6fe6-4ac9-84ec-c865babfcab8","d5047f79-2f05-40f8-86a9-6cb4a813ed07","cef04144-25c1-44e7-ad6e-7f5f564b05ef","3585da81-4f5f-492f-9da3-a3fbf759d91d","1c6b58cf-7892-4808-93ae-6dbb60ecc298","b783808a-2cf8-431f-9345-d4b420ff2cec","08d3b7f5-a9d2-4e9e-9c5c-f6556f5ddbb8","f705d98a-5806-4721-a721-a502ef397f5c","0b1394c3-a8ca-47b3-a187-684d6a145034","3c9d31d8-537e-40f2-b7f2-216c0859da16","080de0fb-96ee-44d0-96a5-51bc5ee55213","54094093-8713-40cf-a8b0-49631e8d91a6","7b904caf-c982-47d4-8de3-1d1ccd86b56e","8e5d85b5-7830-4473-8e40-c607c13b54ba","2047a3bb-e040-4b7b-82b6-bde729dd621a","8588f880-47ff-4daf-8bc6-f38d0d042e19","5c0d184c-90d6-4362-a70f-146080a509e7","4ae3f702-03fe-4114-bf19-3e004b674d38","38d5e84f-c1cd-4974-8d4d-7a0f20cfb88d","2f773a7d-d6f0-4f03-ace9-469ec5ced46d","a8d43bb0-c5f0-45a3-956f-a653df389bdc","9e4ec911-0582-44fe-9676-7a41f7739e01","0e2afed9-0e73-47fa-b652-54438e0c6550","e61d72df-b2a3-4fcb-b5b9-74f69aebac68","f34c5a15-9290-4144-9dcd-f5100777220c","8502a803-448b-41df-8089-513d17573c3e","1469281a-da62-4e78-8a6d-ed5d882547cf","bae7de20-12db-4bb0-80ec-91c424506360","97ece4d4-251c-4d3a-9366-6e5fe4bd799c"],"benchmarkVersion":"4-vector-database-platforms-2026-07-27-models-64232fd32583","providerMatrixVersion":"64232fd32583"}
    Open the source
  • Median citation positionPage median position · observed Sep 12, 2026, 12:00 AM UTC2 position100% confidence
    Source
    Rank.ai Vector Databases Prompt Benchmark
    Grade
    A
    Freshness
    fresh
    Locator
    {"corpusVersion":"vector-database-platforms-2026-07-27","runArtifactIds":["e33dd985-f176-4ab4-9454-aee96d33c088","dcbac240-1491-4352-842c-0806750555ae","0d37b2a2-eb3a-439a-a79f-41e84711c1a4","bf953d93-d4cf-4f60-a020-6d347d999323","071dbba4-9632-433a-b537-174e3f51b2de","ba80dea3-391d-4437-9459-e60a9d2ea270","9124e2fb-1ff5-4d4e-a5a4-f73819f680a0","0bc1d0cf-6fe6-4ac9-84ec-c865babfcab8","d5047f79-2f05-40f8-86a9-6cb4a813ed07","cef04144-25c1-44e7-ad6e-7f5f564b05ef","3585da81-4f5f-492f-9da3-a3fbf759d91d","1c6b58cf-7892-4808-93ae-6dbb60ecc298","b783808a-2cf8-431f-9345-d4b420ff2cec","08d3b7f5-a9d2-4e9e-9c5c-f6556f5ddbb8","f705d98a-5806-4721-a721-a502ef397f5c","0b1394c3-a8ca-47b3-a187-684d6a145034","3c9d31d8-537e-40f2-b7f2-216c0859da16","080de0fb-96ee-44d0-96a5-51bc5ee55213","54094093-8713-40cf-a8b0-49631e8d91a6","7b904caf-c982-47d4-8de3-1d1ccd86b56e","8e5d85b5-7830-4473-8e40-c607c13b54ba","2047a3bb-e040-4b7b-82b6-bde729dd621a","8588f880-47ff-4daf-8bc6-f38d0d042e19","5c0d184c-90d6-4362-a70f-146080a509e7","4ae3f702-03fe-4114-bf19-3e004b674d38","38d5e84f-c1cd-4974-8d4d-7a0f20cfb88d","2f773a7d-d6f0-4f03-ace9-469ec5ced46d","a8d43bb0-c5f0-45a3-956f-a653df389bdc","9e4ec911-0582-44fe-9676-7a41f7739e01","0e2afed9-0e73-47fa-b652-54438e0c6550","e61d72df-b2a3-4fcb-b5b9-74f69aebac68","f34c5a15-9290-4144-9dcd-f5100777220c","8502a803-448b-41df-8089-513d17573c3e","1469281a-da62-4e78-8a6d-ed5d882547cf","bae7de20-12db-4bb0-80ec-91c424506360","97ece4d4-251c-4d3a-9366-6e5fe4bd799c"],"benchmarkVersion":"4-vector-database-platforms-2026-07-27-models-64232fd32583","providerMatrixVersion":"64232fd32583"}
    Open the source
  • Prompt breadthPage prompt breadth · observed Sep 12, 2026, 12:00 AM UTC1 prompts100% confidence
    Source
    Rank.ai Vector Databases Prompt Benchmark
    Grade
    A
    Freshness
    fresh
    Locator
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    Open the source
Public Vector Databases cited-page visibility, version 1-parent-8f2516a7bd0dea82875 observations · 1 source · quality passed
Snapshot
28eb916c-2abb-4fde-94c5-ee310feb436a
Data hash
29d73bacb98e06bcc33c49820ddac38c6af5ae5fcba37dadd82d4b043a0aa520
Method hash
be916b6cd81273c9a5fd551d0ef7adae380b323a6b9101b463316ec7b0bfc9d2

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.