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Comparison

LightRAG vs khoj

LightRAG (Simple and Fast Retrieval-Augmented Generation) vs khoj (Your AI second brain) - live GitHub stats and typed graph relationships, not marketing.

Markdown twin · LightRAG alternatives · khoj alternatives

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LightRAG

HKUDS/LightRAG

37kpushed Jul 8, 2026
vs

khoj

khoj-ai/khoj

36kpushed Jun 24, 2026

Tagline

LightRAG
Simple and Fast Retrieval-Augmented Generation
khoj
Your AI second brain

Stars

LightRAG
37k
khoj
36k

Forks

LightRAG
5.3k
khoj
2.3k

Open issues

LightRAG
228
khoj
117

Language

LightRAG
Python
khoj
Python

Adopt for

LightRAG
LightRAG is a Python library licensed under the MIT License, designed to offer efficient retrieval-augmented generation capabilities for enhancing large language model performance in genAI applications.
khoj
khoj is an AI application that extends personal capabilities via web searches or document retrieval, supporting self-hosting. It can integrate with various tools and formats.

Persona

LightRAG
-
khoj
-

Runtime

LightRAG
-
khoj
-

License

LightRAG
MIT
khoj
AGPL-3.0

Last pushed

LightRAG
Jul 8, 2026
khoj
Jun 24, 2026

Categories

LightRAG
Data & Retrieval, LLM Frameworks
khoj
AI Agents, Evaluation & Observability, Data & Retrieval, Inference & Serving

Trust and health

Maintenance

LightRAG
Very active (96%)
khoj
Active (82%)

Days since push

LightRAG
0d
khoj
13d

Open issues (now)

LightRAG
228
khoj
117

Full report

LightRAG
Trust report

Typed relationship

LightRAG alternative khojKhoj acts as an AI second brain, integrating with RAG-like functionalities for knowledge retrieval and generation, similar to LightRAG.

Choose LightRAG if…

  • License: LightRAG is MIT, khoj is AGPL-3.0.
  • Khoj acts as an AI second brain, integrating with RAG-like functionalities for knowledge retrieval and generation, similar to LightRAG.
  • Tags unique to LightRAG: genai, llm, large-language-models, rag.
  • Also covers LLM Frameworks.
  • When you need quick integration of retrieval-augmented generation into your existing projects without complex setup. LightRAG is built for simplicity and speed which makes it ideal when rapid protypng

When NOT to use LightRAG

  • When you require highly complex and specialized configurations for your retrieval-augmented tasks, as LightRAG emphasizes simplicity over extensive customization.
  • In scenarios where strict control over every aspect of the retrieval process is necessary. Advanced customization options are limited compared to some competitors.
  • For projects with a small dataset or simple tasks that do not benefit significantly from RAG capabilities; LightRAG’s advantages may be underutilized.

Choose khoj if…

  • License: khoj is AGPL-3.0, LightRAG is MIT.
  • Pricing: khoj offers a free self-hosted version. For enterprise-level services with additional support options, pricing details can be found on their official website..
  • Requirements: Min 4 GB RAM; Requires Python environment for self-hosting.; Can also be accessed via its cloud app without local setup..
  • Khoj acts as an AI second brain, integrating with RAG-like functionalities for knowledge retrieval and generation, similar to LightRAG.
  • Tags unique to khoj: assistant, chat, self-hosted, ai.
  • Also covers AI Agents, Evaluation & Observability, Inference & Serving.
  • When you need to personalize your assistant by creating custom agents tailored to specific roles or tasks.

When NOT to use khoj

  • When requiring an out-of-the-box, no-setup-needed AI tool for all use cases as khoj has a significant setup process for full personalization and control.
  • If your primary need is solely image generation or simple document viewing without any customizations or smart notifications, since khoj's strengths lie in its extensive customization options and deep
  • automation capabilities.

Explore

Related comparisons

Common questions

What is the difference between LightRAG and khoj?
LightRAG: Simple and Fast Retrieval-Augmented Generation. khoj: Your AI second brain. See the comparison table for live GitHub stats and shared categories.
When should I choose LightRAG over khoj?
Choose LightRAG over khoj when License: LightRAG is MIT, khoj is AGPL-3.0; Khoj acts as an AI second brain, integrating with RAG-like functionalities for knowledge retrieval and generation, similar to LightRAG; Tags unique to LightRAG: genai, llm, large-language-models, rag; Also covers LLM Frameworks; When you need quick integration of retrieval-augmented generation into your existing projects without complex setup. LightRAG is built for simplicity and speed which makes it ideal when rapid protypng.
When should I choose khoj over LightRAG?
Choose khoj over LightRAG when License: khoj is AGPL-3.0, LightRAG is MIT; Pricing: khoj offers a free self-hosted version. For enterprise-level services with additional support options, pricing details can be found on their official website.; Requirements: Min 4 GB RAM; Requires Python environment for self-hosting.; Can also be accessed via its cloud app without local setup.; Khoj acts as an AI second brain, integrating with RAG-like functionalities for knowledge retrieval and generation, similar to LightRAG; Tags unique to khoj: assistant, chat, self-hosted, ai; Also covers AI Agents, Evaluation & Observability, Inference & Serving; When you need to personalize your assistant by creating custom agents tailored to specific roles or tasks.
When should I avoid LightRAG?
When you require highly complex and specialized configurations for your retrieval-augmented tasks, as LightRAG emphasizes simplicity over extensive customization. In scenarios where strict control over every aspect of the retrieval process is necessary. Advanced customization options are limited compared to some competitors. For projects with a small dataset or simple tasks that do not benefit significantly from RAG capabilities; LightRAG’s advantages may be underutilized.
When should I avoid khoj?
When requiring an out-of-the-box, no-setup-needed AI tool for all use cases as khoj has a significant setup process for full personalization and control. If your primary need is solely image generation or simple document viewing without any customizations or smart notifications, since khoj's strengths lie in its extensive customization options and deep automation capabilities.
Is LightRAG or khoj more popular on GitHub?
LightRAG has more GitHub stars (37,451 vs 35,524). Stars measure visibility, not whether either tool fits your constraints.
Are LightRAG and khoj open source?
Yes - both are open-source projects on GitHub (LightRAG: MIT, khoj: AGPL-3.0).
Where can I find alternatives to LightRAG or khoj?
GraphCanon lists graph-backed alternatives at /tools/hkuds-lightrag/alternatives and /tools/khoj-ai-khoj/alternatives (/tools/hkuds-lightrag/alternatives.md, /tools/khoj-ai-khoj/alternatives.md), ranked by typed relationship edges rather than popularity votes.
Is there a machine-readable version of this comparison?
Yes. The markdown twin at /compare/hkuds-lightrag-vs-khoj-ai-khoj.md mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.
Which is better maintained, LightRAG or khoj?
LightRAG: Very active. khoj: Active. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance.
Where are the full trust reports for LightRAG and khoj?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: LightRAG: /tools/hkuds-lightrag/trust; khoj: /tools/khoj-ai-khoj/trust.

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