Best AI tools for embeddings

Pinecone

Featured

RAG · Hosted vector DB (not an LLM)

8.8

Managed vector database for production-scale similarity search.

Elasticsearch Vector Search

RAG · BYO embeddings (OpenAI, Cohere, Hugging Face, Mistral, Bedrock, Vertex, Azure) plus Elastic's built-in ELSER sparse model and E5 dense model

8.7

Hybrid vector + keyword search in the enterprise-grade Elasticsearch engine

DataStax Astra DB

RAG · Bring-your-own embeddings; integrates with OpenAI, Cohere, Hugging Face, Mistral, NVIDIA NIM, and Vertex AI via server-side vectorize

8.6

Serverless vector and document database for production RAG and AI agents

MongoDB Atlas Vector Search

RAG · Bring-your-own embeddings (OpenAI, Cohere, open models); native Voyage AI embeddings and rerankers

8.6

Vector search built into the operational database you're already using.

LanceDB

RAG

8.2

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

Graphiti

RAG · Multi-model

7.2

Open-source temporal knowledge graph framework for building agent memory that updates in real time.

WeKnora

RAG · Multi-model

7.2

Tencent's open-source RAG framework that turns raw documents into a queryable knowledge base, ReAct agent, and self-maintaining wiki.

BGE (BAAI General Embedding)

RAG · BGE / bge-m3 / bge-reranker

7.1

Open-source embedding and reranker models from BAAI that anchor a huge share of production RAG stacks.

PostgresML

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

7.1

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

Rivestack

RAG · OpenAI embeddings (auto-embeddings)

7.1

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

PageIndex

RAG

7.0

Vectorless reasoning-based retrieval for long documents, with traceable, auditable answers.

Singlebase Cloud

RAG · Multi-model

7.0

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

Superduper

RAG · Multi-model

7.0

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

Cohere

RAG · Command, Embed, Rerank, Transcribe (proprietary)

6.9

Enterprise-grade LLM platform built for private, secure, and customizable deployment.

TurboVec

RAG

6.8

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

Meilisearch

RAG · Retrieval engine (Rust); pluggable embedders including OpenAI, Cohere, Hugging Face, Ollama and custom REST models

Open-source, lightning-fast search engine with built-in hybrid and vector search for RAG

Nomic Atlas

RAG · nomic-embed-text-v1.5, nomic-embed-vision-v1.5 (in-house open-weights); optional integrations with OpenAI, Cohere, and other embedding providers

Interactive maps and embeddings for unstructured text, image, and multimodal data.

Onyx

RAG · LLM-agnostic — routes to OpenAI (GPT-4o/GPT-5), Anthropic Claude, Google Gemini, Azure OpenAI, AWS Bedrock, or local Ollama/vLLM models

Open-source AI chat connected to your docs, apps, and people

Supabase

RAG

Open-source Firebase alternative built on Postgres with a first-class pgvector AI toolkit.

TiDB

RAG

AI-native distributed SQL database with built-in vector search, agent memory, and RAG pipelines

Voyage AI

RAG · in-house (voyage-3.5, voyage-4 series, voyage-code-3, voyage-finance-2, voyage-law-2, voyage-multimodal-3.5, voyage-context-3, rerank-2.5)

State-of-the-art embedding models and rerankers purpose-built for retrieval and RAG.