Best Vector database tools

milvus.io

Best for: AI recommends Milvus most when buyers ask “best managed vector databases for building semantic search and RAG applications” (100% of those answers)

88.6%

95% CI 79–94.1%

62 mentions · avg pos 5

first pick 17.7%

qdrant.tech

Best for: AI recommends Qdrant most when buyers ask “best vector database tools for AI and machine learning applications” (100% of those answers)

88.6%

95% CI 79–94.1%

62 mentions · avg pos 5.5

first pick 11.3%

pinecone.io

Best for: AI recommends Pinecone most when buyers ask “best managed vector databases for building semantic search and RAG applications” (100% of those answers)

85.7%

95% CI 75.7–92.1%

60 mentions · avg pos 3.8

first pick 45%

weaviate.io

Best for: AI recommends Weaviate most when buyers ask “best managed vector databases for building semantic search and RAG applications” (100% of those answers)

82.9%

95% CI 72.4–89.9%

58 mentions · avg pos 5.8

first pick 3.4%

Best for: AI recommends pgvector most when buyers ask “best vector database tools for AI and machine learning applications” (92.3% of those answers)

78.6%

95% CI 67.6–86.6%

55 mentions · avg pos 7.9

first pick 3.6%

postgresql.org

Best for: AI recommends PostgreSQL most when buyers ask “purpose-built vector databases vs vector search extensions on existing databases” (92.3% of those answers)

70%

95% CI 58.5–79.5%

49 mentions · avg pos 9.2

first pick 0%

zilliz.com

Best for: AI recommends Zilliz most when buyers ask “which vector database scales best for billions of embeddings” (84.6% of those answers)

51.4%

95% CI 40–62.8%

36 mentions · avg pos 5.6

first pick 11.1%

Best for: AI recommends HNSW most when buyers ask “how do I choose a vector database for a production RAG pipeline” (76.9% of those answers)

50%

95% CI 38.6–61.4%

35 mentions · avg pos 4

first pick 34.3%

trychroma.com

Best for: AI recommends Chroma most when buyers ask “what should I use as a vector database for my LLM-powered search feature” (100% of those answers)

50%

95% CI 38.6–61.4%

35 mentions · avg pos 10.9

first pick 2.9%

redis.io

Best for: AI recommends Redis most when buyers ask “open-source alternatives to managed vector database platforms” (76.9% of those answers)

45.7%

95% CI 34.6–57.3%

32 mentions · avg pos 11.9

first pick 3.1%

elastic.co

Best for: AI recommends Elasticsearch most when buyers ask “purpose-built vector databases vs vector search extensions on existing databases” (92.3% of those answers)

45.7%

95% CI 34.6–57.3%

32 mentions · avg pos 13.5

first pick 0%

mongodb.com

Best for: AI recommends MongoDB most when buyers ask “purpose-built vector databases vs vector search extensions on existing databases” (84.6% of those answers)

42.9%

95% CI 31.9–54.5%

30 mentions · avg pos 11.1

first pick 6.7%

Best for: AI recommends Postgres most when buyers ask “open-source alternatives to managed vector database platforms” (53.8% of those answers)

37.1%

95% CI 26.8–48.9%

26 mentions · avg pos 8.2

first pick 7.7%

opensearch.org

Best for: AI recommends OpenSearch most when buyers ask “best vector database tools for AI and machine learning applications” (46.2% of those answers)

31.4%

95% CI 21.8–43%

22 mentions · avg pos 13.4

first pick 0%

vespa.ai

Best for: AI recommends Vespa most when buyers ask “best vector database tools for AI and machine learning applications” (38.5% of those answers)

22.9%

95% CI 14.6–34%

16 mentions · avg pos 10.5

first pick 0%

firecrawl.dev

Best for: AI recommends Firecrawl most when buyers ask “best vector database tools for AI and machine learning applications” (53.8% of those answers)

21.4%

95% CI 13.4–32.4%

15 mentions · avg pos 9.4

first pick 6.7%

zenml.io

Best for: AI recommends ZenML most when buyers ask “how do I choose a vector database for a production RAG pipeline” (46.2% of those answers)

21.4%

95% CI 13.4–32.4%

15 mentions · avg pos 15

first pick 6.7%

faiss.ai

Best for: AI recommends FAISS most when buyers ask “open-source alternatives to managed vector database platforms” (61.5% of those answers)

18.6%

95% CI 11.2–29.2%

13 mentions · avg pos 7.9

first pick 23.1%

qdrant.io

Best for: AI recommends Qdrant Cloud most when buyers ask “best managed vector databases for building semantic search and RAG applications” (69.2% of those answers)

17.1%

95% CI 10.1–27.6%

12 mentions · avg pos 8.9

first pick 0%

lancedb.com

Best for: AI recommends LanceDB most when buyers ask “open-source alternatives to managed vector database platforms” (53.8% of those answers)

15.7%

95% CI 9–26%

11 mentions · avg pos 12.6

first pick 0%

langchain.com

Best for: AI recommends LangChain most when buyers ask “how do I choose a vector database for a production RAG pipeline” (38.5% of those answers)

15.7%

95% CI 9–26%

11 mentions · avg pos 14.4

first pick 9.1%

llamaindex.ai

Best for: AI recommends LlamaIndex most when buyers ask “how do I choose a vector database for a production RAG pipeline” (30.8% of those answers)

14.3%

95% CI 7.9–24.3%

10 mentions · avg pos 17.1

first pick 10%

Best for: AI recommends pgvectorscale most when buyers ask “purpose-built vector databases vs vector search extensions on existing databases” (38.5% of those answers)

12.9%

95% CI 6.9–22.7%

9 mentions · avg pos 8

first pick 0%

Best for: AI recommends Turbopuffer most when buyers ask “best managed vector databases for building semantic search and RAG applications” (30.8% of those answers)

12.9%

95% CI 6.9–22.7%

9 mentions · avg pos 12.9

first pick 0%

datacamp.com

Best for: AI recommends DataCamp most when buyers ask “best managed vector databases for building semantic search and RAG applications” (46.2% of those answers)

12.9%

95% CI 6.9–22.7%

9 mentions · avg pos 16

first pick 0%

instaclustr.com

Best for: AI recommends Instaclustr most when buyers ask “open-source alternatives to managed vector database platforms” (46.2% of those answers)

10%

95% CI 4.9–19.2%

7 mentions · avg pos 10

first pick 0%

dev.to

Best for: AI recommends Dev.to most when buyers ask “purpose-built vector databases vs vector search extensions on existing databases” (46.2% of those answers)

10%

95% CI 4.9–19.2%

7 mentions · avg pos 13

first pick 0%

8.6%

95% CI 4–17.5%

6 mentions · avg pos 10.2

first pick 0%

8.6%

95% CI 4–17.5%

6 mentions · avg pos 19.2

first pick 0%

5.7%

95% CI 2.2–13.8%

4 mentions · avg pos 2.8

first pick 25%

Best for: AI recommends Faiss (Facebook AI Similarity Search) most when buyers ask “best vector database tools for AI and machine learning applications” (38.5% of those answers)

5.7%

95% CI 2.2–13.8%

4 mentions · avg pos 7

first pick 50%

Best for: AI recommends DiskANN most when buyers ask “which vector database scales best for billions of embeddings” (38.5% of those answers)

4.3%

95% CI 1.5–11.9%

3 mentions · avg pos 1

first pick 33.3%

lakefs.io

Best for: AI recommends lakeFS most when buyers ask “what should I use as a vector database for my LLM-powered search feature” (30.8% of those answers)

4.3%

95% CI 1.5–11.9%

3 mentions · avg pos 1

first pick 33.3%

yugabyte.com

Best for: AI recommends YugabyteDB most when buyers ask “which vector database scales best for billions of embeddings” (46.2% of those answers)

4.3%

95% CI 1.5–11.9%

3 mentions · avg pos 4

first pick 0%

databricks.com

4.3%

95% CI 1.5–11.9%

3 mentions · avg pos 4.3

first pick 0%

pingcap.com

Best for: AI recommends TiDB Vector Search most when buyers ask “how do I choose a vector database for a production RAG pipeline” (30.8% of those answers)

4.3%

95% CI 1.5–11.9%

3 mentions · avg pos 9.5

first pick 0%

aws.amazon.com

4.3%

95% CI 1.5–11.9%

3 mentions · avg pos 13

first pick 0%

supabase.com

4.3%

95% CI 1.5–11.9%

3 mentions · avg pos 24.3

first pick 0%

neon.tech

2.9%

95% CI 0.8–9.8%

2 mentions · avg pos 3

first pick 0%

2.9%

95% CI 0.8–9.8%

2 mentions · avg pos 25.5

first pick 0%

ibm.com

2.9%

95% CI 0.8–9.8%

2 mentions

first pick 0%

cloud.google.com

1.4%

95% CI 0.3–7.7%

1 mentions · avg pos 2

first pick 0%

vectara.com

1.4%

95% CI 0.3–7.7%

1 mentions · avg pos 9

first pick 0%

azure.microsoft.com

1.4%

95% CI 0.3–7.7%

1 mentions · avg pos 15

first pick 0%

aerospike.com

1.4%

95% CI 0.3–7.7%

1 mentions · avg pos 18

first pick 0%

1.4%

95% CI 0.3–7.7%

1 mentions · avg pos 34

first pick 0%

atlan.com

1.4%

95% CI 0.3–7.7%

1 mentions

first pick 0%

couchbase.com

1.4%

95% CI 0.3–7.7%

1 mentions

first pick 0%

fast.io

1.4%

95% CI 0.3–7.7%

1 mentions

first pick 0%

liveblocks.io

1.4%

95% CI 0.3–7.7%

1 mentions

first pick 0%

nvidia.com

1.4%

95% CI 0.3–7.7%

1 mentions

first pick 0%

northflank.com

1.4%

95% CI 0.3–7.7%

1 mentions

first pick 0%

openalternative.co

1.4%

95% CI 0.3–7.7%

1 mentions

first pick 0%

openmetal.io

1.4%

95% CI 0.3–7.7%

1 mentions

first pick 0%

1.4%

95% CI 0.3–7.7%

1 mentions

first pick 0%

sourceforge.net

1.4%

95% CI 0.3–7.7%

1 mentions

first pick 0%

timescale.com

1.4%

95% CI 0.3–7.7%

1 mentions

first pick 0%

x.com

1.4%

95% CI 0.3–7.7%

1 mentions

first pick 0%