About Vector Databases & Embeddings Infrastructure
The Vector Databases & Embeddings Infrastructure category is part of the AI Memory & Context market map, tracking 16 companies building in this segment. Long-term memory systems, persistent context windows, retrieval-augmented memory, and personalization layers giving AI continuity across sessions and tasks. Curated by Hartmann Capital's venture research team.
Companies in Vector Databases & Embeddings Infrastructure
- Pinecone — Secondary, $238M
- Weaviate — Series B, $68M
- Qdrant — Series A, $28M
- Chroma — Seed, $18M
- Zilliz — Series C, $113M
- Marqo — Series A, $12.5M
- Turbopuffer — Seed, $15M
- LanceDB — Series A, $11M
- Vespa — Open Source
- Jina AI — Series A, $37.5M
- Cohere — Series D, $1.6B
- Voyage AI — Acquired
- Nomic — Series A, $17M
- Tessel AI — Seed
- pgvector — Open Source
- Supabase — Series E, $116M
Frequently Asked Questions
- What companies are in the Vector Databases & Embeddings Infrastructure category?
- The Vector Databases & Embeddings Infrastructure category includes 16 companies: Pinecone, Weaviate, Qdrant, Chroma, Zilliz, Marqo, Turbopuffer, LanceDB, Vespa, Jina AI, Cohere, Voyage AI, Nomic, Tessel AI, pgvector, Supabase. This is part of the AI Memory & Context market map maintained by Hartmann Capital.
- How many Vector Databases & Embeddings Infrastructure startups are tracked?
- Hartmann Capital tracks 16 companies in the Vector Databases & Embeddings Infrastructure segment of the AI Memory & Context market map.
- What are the best funded Vector Databases & Embeddings Infrastructure companies?
- Top funded companies in Vector Databases & Embeddings Infrastructure include Cohere ($1600M), Pinecone ($238M), Supabase ($116M), Zilliz ($113M), Weaviate ($68M). Browse the full list in the AI Memory & Context market map.
- How can I submit my startup?
- You can submit your startup for inclusion by visiting the submission page. Submissions are reviewed by Hartmann Capital's research team.