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235 tools · 33 stacks

AI tools are all over the place. This is the full landscape — 247 tools across 21 categories, mapped and connected. Ready to narrow it down? Build your stack →

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These tools integrates with
LightRAG
vs
Qdrant

Choose LightRAG when…

  • •Your queries require reasoning across multiple documents or topics
  • •You want graph-based retrieval instead of flat vector search
  • •You need both fact-level and concept-level retrieval in one system

Choose Qdrant when…

  • •You need high-performance vector search in production
  • •You want OSS with Rust-level performance
  • •Filtering alongside vector search is important
Field
LightRAG
Qdrant
Category
Pipelines & RAG
LLM Infrastructure
Type
OSS
OSS
Free Tier
✓ Yes
✓ Yes
Plans
—
Cloud: Usage-based
Stars
⭐ 15,000
⭐ 20,000
Health
●85 — Active
●95 — Active
Trajectory
— not enough data
— not enough data
Synced
today
today

LightRAG

RAG framework that builds a knowledge graph from documents, enabling retrieval at both local (specific facts) and global (thematic) levels. Outperforms naive RAG on complex questions requiring reasoning across multiple document sections. EMNLP 2025.

Qdrant

Rust-based vector database optimized for filtering. Supports named vectors, payloads, and hybrid search. Self-hostable or cloud.

LightRAG Website ↗GitHub ↗
Qdrant Website ↗GitHub ↗

Shared Connections (1)

LlamaIndex

Only LightRAG (2)

QdrantOpenAI API

Only Qdrant (13)

LangGraphLangChainHaystackDifyVercel AI SDKChromaPineconepgvector
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