LightRAG
A lightweight framework that combines knowledge graphs and vector embeddings for efficient information retrieval
- Also known as
- lightrag
What is LightRAG?
An open-source RAG system designed for high scalability that uses both knowledge graphs and vector search to retrieve information from large datasets with reduced computational overhead and faster response times.
LightRAG pricing
We don't have LightRAG's full plan breakdown yet (its pricing page resisted automated reading). Here's what we could confirm. Always check live pricing for exact numbers.
What LightRAG does
The capabilities that matter for rag tools, normalised so it lines up with every alternative. “-” means we haven't confirmed it, not that it's missing.
- Hybrid retrieval
- ✓
- Reranking integration
- ✓
- Multi hop agentic retrieval
- ✗
- Embedding provider agnostic
- ✓
- LLM provider agnostic
- ✓
- Built in rag eval metrics
- -
- Citation attribution
- ✓
- Multimodal rag
- ✓
- Managed ingestion pipeline
- ✓
- Open source
- ✓
Platform & deployment
Independently observed- CLI
- macOS
- Web
- Linux
- On-premise
- Self-hosted
Integrations (9)
Independently observed- PostgreSQL•
- Neo4j•
- MongoDB•
- Milvus•
- Qdrant•
- Redis•
- Memgraph•
- MinerU•
- Docling•
Security & compliance
Known vulnerabilities: 10 (9 in the last 12 months), max severity CRITICAL sourcea count reflects scale & disclosure, not quality
LightRAG FAQ
Common questions about LightRAG, answered from independent, dated evidence.
What is LightRAG?
A lightweight RAG system that processes documents through flexible parsing engines and supports local deployment of embedding, reranking, and storage backends. Includes built-in citation attribution and can work with various open-source LLMs and embedding models. It is indexed under RAG Tools.
Source: https://github.com/pricing
What platforms does LightRAG support?
LightRAG supports the web and a command-line interface. Platforms we have not confirmed are simply not listed here rather than ruled out.
Source: https://github.com/pricing
Can LightRAG be self-hosted?
Yes. LightRAG can be deployed cloud / SaaS, on-premise and self-hosted, so it does not have to run on the vendor's infrastructure.
Source: https://github.com/pricing
Is LightRAG open source?
Yes. LightRAG is published under the MIT licence, a permissive licence that generally allows commercial use and modification. Licence terms can change between releases, so verify against the repository for the version you intend to use.
LightRAG alternatives
Other rag tools we track, ranked by the same independent score.
- RagieA managed AI context platform for agents, assistants, and applicationsmedium · 73%
- Amazon Bedrock Knowledge BasesA managed service connecting AI applications to enterprise data with automatic indexing and retrievalmedium · 74%
- PathwayA streaming data framework for building real-time AI and ML applicationslow · 35%
- Ragaslow · 32%
- RAGFlowAn open-source platform combining retrieval-augmented generation with AI agent capabilities to provide contextual support for language modelslow · 9%
- Contextual AImedium · 61%
Compare LightRAG
Side by side against other rag tools, attribute by attribute, with a source on every value.
The vioscaleAI score: one lens on the evidence
Not user reviews and not a paid placement: a confidence-weighted blend of the independent signals below (adoption, activity, security posture, and more), which you can sort and re-weight yourself. Vendors can correct their listing but can never move their rank, and stars are weighted low as a vanity metric. It is one way to read the evidence for LightRAG, not the verdict.
| Signal | Score | Weight | Contribution | Evidence |
|---|---|---|---|---|
| Development activity | 63 | 0.14 | 8.5 | ✓ |
| Release cadence | 96 | 0.08 | 7.8 | ✓ |
| Capabilities | 92 | 0.08 | 7.4 | ✓ |
| Stars | 87 | 0.05 | 4.1 | ✓ |
| Integrations | 29 | 0.05 | 1.6 | ✓ |
| Dependent projects | 0 | 0.05 | 0.0 | ✓ |
| Security posture | 5 | 0.12 | 0.0 | - |
| Package downloads | 0 | 0.04 | 0.0 | - |
| Security score | 0 | 0.05 | 0.0 | - |
| Developer Q&A activity | 0 | 0.14 | 0.0 | - |
Computed . Re-weight it by intent, or see the full method.
All data & sourcesshow ↓
Every value we hold, with its source, retrieval date, and confidence. This is the evidence behind the score: don't trust it, verify it.
Activity
| Attribute | Value | Evidence |
|---|---|---|
| Commits last 30d | 100 | mediumsource · 2026-10-14 · 65% |
Adoption
Content
| Attribute | Value | Evidence |
|---|---|---|
| Faq | 4 items | mediumsource · 2026-09-10 · 69% |
Features
| Attribute | Value | Evidence |
|---|---|---|
| Capabilities | Open source, Multimodal rag, Hybrid retrieval, Citation attribution, Llm provider agnostic, Reranking integration, Managed ingestion pipeline, Embedding provider agnostic | mediumsource · 2026-10-14 · 60% |
Integrations
| Attribute | Value | Evidence |
|---|---|---|
| Count | 9 | mediumsource · 2026-09-14 · 60% |
Language
| Attribute | Value | Evidence |
|---|---|---|
| Primary | Python | highsource · 2026-10-14 · 90% |
License
| Attribute | Value | Evidence |
|---|---|---|
| Spdx | MIT | highsource · 2026-10-14 · 95% |
Pricing
Release
Security
| Attribute | Value | Evidence |
|---|---|---|
| Vulnerabilities | Count: 10 · Source: https://advisories.ecosyste.ms/api/v1/advisories?ecosystem=pypi&package_name=lightrag-hku&per_page=100 · Last 12m: 9 · Max severity: CRITICAL | highsource · 2026-10-14 · 90% |
| Trust center | https://github.com/HKUDS/LightRAG/security | mediumsource · 2026-10-14 · 60% |
| Disclosure policy | Yes | mediumsource · 2026-10-14 · 60% |
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