Comparison
ragflow vs llama_index
Verdict
Pick ragflow if rAGFlow is an open-source RAG engine that integrates agent capabilities to enhance context management for LLMs, built in Go under the Apache-2.0 license; pick llama_index if llamaIndex is an open-source framework for building AI-powered document processing applications, including RAG and agent applications, with a focus on document parsing and extraction. It offers over 300 integration packs.
Markdown twin · ragflow alternatives · llama_index alternatives
GraphCanon updated Sep 30, 2026
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Trust & integrity
| Signal | ragflow | llama_index |
|---|---|---|
| Maintenance | Very active (0d since push) As of Sep 18, 2026 · github_public_v1 | Very active (0d since push) As of Sep 18, 2026 · github_public_v1 |
| Provenance | Not a fork · Organization account As of Sep 18, 2026 · github_public_v1 | Not a fork · Organization account As of Sep 18, 2026 · github_public_v1 |
| OSV dependency advisories | Published findings As of Sep 18, 2026 · osv@v1 | No lockfile (source not queried) As of Sep 18, 2026 · osv@v1 |
| deps.dev advisories | Not queried deps.dev@v1 | Not queried deps.dev@v1 |
| OpenSSF Scorecard | Not queried openssf-scorecard@v1 | Not queried openssf-scorecard@v1 |
Tagline
- ragflow
- Retrieval-Augmented Generation (RAG) engine with agent capabilities
- llama_index
- Document processing platform for AI
Stars
- ragflow
- 91k
- llama_index
- 52k
Forks
- ragflow
- 11k
- llama_index
- 8.2k
Open issues
- ragflow
- 1.4k
- llama_index
- 802
Language
- ragflow
- Go
- llama_index
- Python
Adopt for
- ragflow
- RAGFlow is an open-source RAG engine that integrates agent capabilities to enhance context management for LLMs, built in Go under the Apache-2.0 license.
- llama_index
- LlamaIndex is an open-source framework for building AI-powered document processing applications, including RAG and agent applications, with a focus on document parsing and extraction. It offers over 300 integration packs
Persona
- ragflow
- -
- llama_index
- -
Runtime
- ragflow
- -
- llama_index
- -
License
- ragflow
- Apache-2.0
- llama_index
- MIT
Last pushed
- ragflow
- Sep 18, 2026
- llama_index
- Sep 18, 2026
Categories
- ragflow
- AI Agents, Data & Retrieval
- llama_index
- AI Agents, Data & Retrieval, Developer Tools, Model Training
Trust and health
Open issues (now)
- ragflow
- 1.4k
- llama_index
- 802
Stars delta
- ragflow
- +4.4k (30d)
- llama_index
- +765 (30d)
Open issues delta
- ragflow
- -553 (30d)
- llama_index
- +187 (30d)
OSV dependency advisories
- ragflow
- Published findings
- llama_index
- No lockfile (source not queried)
Full report
- ragflow
- Trust report
- llama_index
- Trust report
Typed relationship
ragflow alternative llama_indexIn both cases, they are tools for Retrieval-Augmented Generation with agent capabilities. However, RagFlow integrates directly into existing workflows, making it an alternative approach.
Choose ragflow if…
- ragflow is primarily Go; llama_index is Python.
- License: ragflow is Apache-2.0, llama_index is MIT.
- In both cases, they are tools for Retrieval-Augmented Generation with agent capabilities. However, RagFlow integrates directly into existing workflows, making it an alternative approach.
- Tags unique to ragflow: agent-harness, agentic-ai, agentic-retrieval, agentic-search.
- ragflow ships Docker support for self-hosted deployment.
- When you need an open-source RAG engine that can integrate with external LLM and embedding services to enhance context management.
When NOT to use ragflow
- If your project does not require integration with external LLM and embedding services, as RAGFlow relies on these services.
- If you are looking for a lightweight solution, as RAGFlow's Docker image is approximately 2 GB in size.
- When you prefer tools that do not require building a Docker image, as RAGFlow's setup involves creating a Docker image.
Choose llama_index if…
- llama_index is primarily Python; ragflow is Go.
- License: llama_index is MIT, ragflow is Apache-2.0.
- In both cases, they are tools for Retrieval-Augmented Generation with agent capabilities. However, RagFlow integrates directly into existing workflows, making it an alternative approach.
- Tags unique to llama_index: agents, application, data, fine-tuning.
- Also covers Developer Tools, Model Training.
- When you need a framework that focuses on document parsing and extraction, as LlamaIndex has evolved to prioritize these capabilities
When NOT to use llama_index
- If your project requires enterprise-level features such as agentic OCR, as LlamaIndex's primary focus has shifted towards LlamaParse, an enterprise platform
- When you need a tool that is actively developed and maintained as the primary focus of the company has shifted towards LlamaParse and LiteParse, and the OSS framework is now a secondary focus
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (infiniflow/ragflow) · observed Sep 20, 2026
- GitHub forks (infiniflow/ragflow) · observed Sep 20, 2026
- Last push (infiniflow/ragflow) · observed Sep 18, 2026
- License file (Apache-2.0) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Sep 18, 2026
- Trust scan (lockfile / OSV) · observed Sep 18, 2026
- GitHub stars (run-llama/llama_index) · observed Sep 20, 2026
- GitHub forks (run-llama/llama_index) · observed Sep 20, 2026
- Last push (run-llama/llama_index) · observed Sep 18, 2026
- License file (MIT) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Sep 18, 2026
- Trust scan (lockfile / OSV) · observed Sep 18, 2026
GitHub stars on cards: ragflow 91k · llama_index 52k (synced Sep 20, 2026).
Common questions
- What is the difference between ragflow and llama_index?
- ragflow: Retrieval-Augmented Generation (RAG) engine with agent capabilities. llama_index: Document processing platform for AI. See the comparison table for live GitHub stats and shared categories.
- When should I choose ragflow over llama_index?
- Choose ragflow over llama_index when ragflow is primarily Go; llama_index is Python; License: ragflow is Apache-2.0, llama_index is MIT; In both cases, they are tools for Retrieval-Augmented Generation with agent capabilities. However, RagFlow integrates directly into existing workflows, making it an alternative approach; Tags unique to ragflow: agent-harness, agentic-ai, agentic-retrieval, agentic-search; ragflow ships Docker support for self-hosted deployment; When you need an open-source RAG engine that can integrate with external LLM and embedding services to enhance context management.
- When should I choose llama_index over ragflow?
- Choose llama_index over ragflow when llama_index is primarily Python; ragflow is Go; License: llama_index is MIT, ragflow is Apache-2.0; In both cases, they are tools for Retrieval-Augmented Generation with agent capabilities. However, RagFlow integrates directly into existing workflows, making it an alternative approach; Tags unique to llama_index: agents, application, data, fine-tuning; Also covers Developer Tools, Model Training; When you need a framework that focuses on document parsing and extraction, as LlamaIndex has evolved to prioritize these capabilities.
- When should I avoid ragflow?
- If your project does not require integration with external LLM and embedding services, as RAGFlow relies on these services. If you are looking for a lightweight solution, as RAGFlow's Docker image is approximately 2 GB in size. When you prefer tools that do not require building a Docker image, as RAGFlow's setup involves creating a Docker image.
- When should I avoid llama_index?
- If your project requires enterprise-level features such as agentic OCR, as LlamaIndex's primary focus has shifted towards LlamaParse, an enterprise platform When you need a tool that is actively developed and maintained as the primary focus of the company has shifted towards LlamaParse and LiteParse, and the OSS framework is now a secondary focus
- Is ragflow or llama_index more popular on GitHub?
- ragflow has more GitHub stars (90,923 vs 52,207). Stars measure visibility, not whether either tool fits your constraints.
- Are ragflow and llama_index open source?
- Yes - both are open-source projects on GitHub (ragflow: Apache-2.0, llama_index: MIT).
- Where can I find alternatives to ragflow or llama_index?
- GraphCanon lists graph-backed alternatives at ragflow alternatives and llama_index alternatives (ragflow markdown twin, llama_index markdown twin), ranked by typed relationship edges rather than popularity votes.
- Is there a machine-readable version of this comparison?
- Yes. The markdown twin at this comparison mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.
- Which is better maintained, ragflow or llama_index?
- ragflow: Very active. llama_index: Very 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 ragflow and llama_index?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: ragflow trust report; llama_index trust report.