What is the best vector database for handling unstructured PDF documents with complex tables and metadata for an enterprise knowledge base we are launching this week?
Download run
Fan-out diagram
The searches the AI actually ran for this prompt.
SEED QUERY
What is the best vector database for handling unstructured PDF documents with complex tables and metadata for an enterprise knowledge base we are launching this week?
5 real searches · 1 real-search pass
2026 enterprise vector database comparison Pinecone Weaviate Qdrant Azure AI Search hybrid search metadata filtering documentationGoogle ↗
OBSERVEDOther / navigational
Azure AI Search Document Intelligence PDF layout tables extraction vector search integrated vectorization documentation 2026Google ↗
OBSERVEDOther / navigational
Pinecone documentation hybrid search metadata filtering enterprise security 2026Google ↗
OBSERVEDOther / navigational
Weaviate documentation hybrid search filters multi tenancy enterprise 2026Google ↗
OBSERVEDOther / navigational
Qdrant documentation hybrid queries payload filtering enterprise cloud 2026Google ↗
OBSERVEDOther / navigational
Badge and edge weight = share of passes that produced the query. Hover a query for its intent and routing format.
Query classes
Google's semantic query class for every sub-query: what kind of answer each search is after, simulated vs real.
ChatGPT real searches (5)
Classes come from the query-classifier (a local Laya model). 5 of 5 calls are low-confidence (under 50%) — hover a query in the table to see its confidence.
Searches and sources
ChatGPT5 real searches · gpt-6
2026 enterprise vector database comparison Pinecone Weaviate Qdrant Azure AI Search hybrid search metadata filtering documentation Google ↗
Azure AI Search Document Intelligence PDF layout tables extraction vector search integrated vectorization documentation 2026 Google ↗
Pinecone documentation hybrid search metadata filtering enterprise security 2026 Google ↗
Weaviate documentation hybrid search filters multi tenancy enterprise 2026 Google ↗
Qdrant documentation hybrid queries payload filtering enterprise cloud 2026 Google ↗
- Integrated Vectorization Overview - Azure AI Search · learn.microsoft.com
- Chunk and Vectorize by Document Layout (Document Layout Skill) - Azure AI Search · learn.microsoft.com
- Multimodal Search Concepts and Guidance - Azure AI Search · learn.microsoft.com
- Hybrid Queries · qdrant.tech
- Qdrant Fundamentals · qdrant.tech
- Azure Document Intelligence and Azure Content Understanding: a practical guide · devblogs.microsoft.com
- azure-ai-docs/articles/ai-services/document-intelligence/prebuilt/layout.md at main · MicrosoftDocs/azure-ai-docs · github.com
Queries
5 queries · click a column to sort
| Query / type | Search | Intent | Query class | Routing format | Cluster | Freq ↓ | Weight |
|---|---|---|---|---|---|---|---|
2026 enterprise vector database comparison Pinecone Weaviate Qdrant Azure AI Search hybrid search metadata filtering documentation OBSERVED | Google ↗ AI Mode ↗ | — | Other / navigational | — | — | 1x of 1 | |
Azure AI Search Document Intelligence PDF layout tables extraction vector search integrated vectorization documentation 2026 OBSERVED | Google ↗ AI Mode ↗ | — | Other / navigational | — | — | 1x of 1 | |
Pinecone documentation hybrid search metadata filtering enterprise security 2026 OBSERVED | Google ↗ AI Mode ↗ | — | Other / navigational | — | — | 1x of 1 | |
Weaviate documentation hybrid search filters multi tenancy enterprise 2026 OBSERVED | Google ↗ AI Mode ↗ | — | Other / navigational | — | — | 1x of 1 | |
Qdrant documentation hybrid queries payload filtering enterprise cloud 2026 OBSERVED | Google ↗ AI Mode ↗ | — | Other / navigational | — | — | 1x of 1 |