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Vector database9 of 5720 tools

9 tools filed under Vector database by what their own homepage shows, ranked by who uses them among those still maintained.

A tag is one of thirty-odd words from a closed list, chosen by the same reader from the same page as the line — never a keyword the vendor supplied.

Ranked by use

By tag
  • Pinecone

    pinecone.io

    Stores and retrieves vector embeddings at scale for retrieval-augmented generation and agent knowledge systems.

    Retrieval (RAG)From $20/mo

    Widely usedsince 2019

    #98 of 3977
  • SurrealDB

    surrealdb.com

    Stores documents, graphs, vectors, and relational data in one engine with built-in agent memory layer.

    EstablishedActively maintainedsince 2015

    #141 of 3977
  • Zilliz

    zilliz.com

    Manages vector data for AI applications with real-time search, discovery, and analytics on a single platform.

    Retrieval (RAG)From $126/mo

    Establishedsince 2017

    #247 of 3977
  • Qdrant

    qdrant.tech

    Stores and searches vectors at scale with metadata filtering, hybrid search, and reranking.

    Establishedsince 2021

    #254 of 3977
  • Weaviate

    weaviate.io

    Vector database that stores, indexes, and searches high-dimensional vectors for retrieval-augmented generation and semantic search.

    Retrieval (RAG)From $45/mo

    Established

    #288 of 3977
  • turbopuffer

    turbopuffer.com

    Vector and full-text search database built on object storage, scaling to 256TB per index with sub-10ms latency.

    Retrieval (RAG)From $16/mo

    Established

    #450 of 3977
  • YantrikDB

    yantrikdb.com

    Persistent memory database for AI agents that stores and retrieves facts across sessions with conflict detection.

    Emerging

    #1614 of 3977
  • zinfradb

    zinfradb.com

    Stores and searches vectors, graphs, and text in a single database binary.

    Emerging

    #3053 of 3977
  • Supermemory MCP

    supermemory.ai

    Stores and retrieves learned context for agents using a vector graph database, injecting relevant memories into model prompts in real time.

    LLM operationsFrom $19/mo

    not read yet

How we read a tool

No votes, no reviews, no vendor claims. Every week a crawler reads each tool's own site and a few public registries, and the words on the card are bands over what it read.

  • Use: visits to the site (estimated), installs from npm and PyPI, presence in Chrome's usage report.
  • Activity: the newest release on GitHub, npm or PyPI; the newest dated page on the site; open roles on a public jobs board.
  • Price: the vendor's own pricing page, read with the date. A figure is printed only when it is on that page.
  • The line and the use cases are written by us from the homepage, one row at a time, and refused when they repeat the vendor's marketing.

How AI assistants read each site — the reading vendors ask us about — is on each tool's own visibility page.