Infinity
Die KI-native Datenbank für LLM-Anwendungen – extrem schnelle hybride Suche für dichte Vektoren, dünnbesetzte Vektoren, Tensoren (Multi-Vektoren) und Volltext für RAG-Pipelines
Überblick
Anforderungen
Empfohlener VPS
Hostinger · KVM 4
4 vCPU · 16384 MB · 200 GB
Hostinger · KVM 4
4 vCPU · 16384 MB · 200 GB
Hostinger · KVM 8
8 vCPU · 32256 MB · 400 GB
Affiliate-Hinweis
Docker Compose
# Generated by Run This Ai — docker-compose.yml
services:
infinity:
image: infiniflow/infinity:latest
restart: unless-stopped
ports:
- 8080:8080
volumes:
- ./data/infinity:/data
Verwandte Tools
LangChain
Build context-aware reasoning applications powered by LLMs
Supabase
Open-source Postgres platform for AI apps with vector search, realtime subscriptions & built-in dashboard
RedisStack
Redis with integrated modules for vector search, JSON, and search capabilities
Meilisearch
Lightning-fast search engine with AI-powered hybrid and vector search
PrivateGPT
Chat with your documents privately using LLMs — 100% local, no data leaks
Milvus
High-performance cloud-native vector database for scalable ANN search
Anleitungen & Artikel
Getting Started with Infinity: A Developer's Guide to Hybrid Search with Dense, Sparse, and Full-Text Queries
Step-by-step tutorial for setting up Infinity — from Docker deployment to hybrid search with dense vectors, sparse vectors, and full-text using Python SDK.
Infinity: The AI-Native Database Powering Next-Gen RAG with Hybrid Search in a Single Engine
Discover Infinity — the open-source AI-native database that combines dense vector, sparse vector, tensor (multi-vector), and full-text search in a single unified engine for production RAG pipelines.