Best AI tools for vector databases

Pinecone

Featured

RAG · Hosted vector DB (not an LLM)

8.8

Managed vector database for production-scale similarity search.

Agentset

RAG · Multi-model (Claude, OpenAI, Google, xAI, Cohere, Mistral, DeepSeek)

Production-ready RAG infrastructure with agentic search, citations, and model-agnostic plumbing.

Context Data

RAG · Multi-model

Enterprise data platform for deploying private RAG pipelines without infrastructure plumbing.

Epsilla

RAG · Multi-model

Agent-as-a-Service platform with managed RAG and a no-code builder for vertical enterprise AI.

Feast

RAG

Open-source feature store that serves consistent features to ML training and online inference, with RAG vector search built in.

HelixDB

RAG

Unified graph-and-vector database built for AI agent memory and GraphRAG.

LanceDB

RAG

Open-source multimodal lakehouse and vector database built for AI training and retrieval at petabyte scale.

PostgresML

RAG · Multi-model (Llama, Mistral, open-source embeddings)

PostgreSQL extension that runs embeddings, vector search, and LLM inference inside your database.

Rivestack

RAG · OpenAI embeddings (auto-embeddings)

Managed Postgres with pgvector on dedicated NVMe, pitched as a cheaper RAG backend than Pinecone or Supabase.

Singlebase Cloud

RAG · Multi-model

AI-native Firebase alternative bundling document DB, vector DB, auth, storage, and built-in AI services.

Superduper

RAG · Multi-model

Enterprise AI agent orchestration that brings RAG and agents to your existing data stack without migration.

TurboVec

RAG

Rust-powered vector index with 2-4 bit TurboQuant compression for SIMD-accelerated RAG search.