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Comparison

kotaemon vs ragflow

Verdict

Pick kotaemon if cinnamon's kotaemon is an open-source Retrieval-Augmented Generation-based chat tool that facilitates document interaction through a user-friendly chat interface; pick ragflow if rAGFlow is a Retrieval-Augmented Generation (RAG) engine that integrates AI agents for enhanced context management in LLM applications, built using Go language and released under the Apache-2.0 license.

Markdown twin · kotaemon alternatives · ragflow alternatives

GraphCanon updated 4d

kotaemon logo

kotaemon

Cinnamon/kotaemon

★ 26kpushed Jul 14, 2026
vs
ragflow logo

ragflow

infiniflow/ragflow

★ 87kpushed Jul 31, 2026

Trust & integrity

Signalkotaemonragflow
Maintenance
Steady (34d since push)
As of 4d · github_public_v1
Very active (0d since push)
As of 3w · github_public_v1
Provenance
Not a fork · Organization account
As of 4d · github_public_v1
Not a fork · Organization account
As of 3w · github_public_v1
OSV dependency advisories
No lockfile (source not queried)
As of 1mo · osv@v1
Published findings
As of 1mo · 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
kotaemon trust reportragflow trust reportTrust methodology

Tagline

kotaemon
An open-source RAG-based tool for chatting with your documents.
ragflow
Retrieval-Augmented Generation engine with agent capabilities

Stars

kotaemon
26k
ragflow
87k

Forks

kotaemon
2.1k
ragflow
10k

Open issues

kotaemon
241
ragflow
2.0k

Language

kotaemon
Python
ragflow
Go

Adopt for

kotaemon
Cinnamon's kotaemon is an open-source Retrieval-Augmented Generation-based chat tool that facilitates document interaction through a user-friendly chat interface.
ragflow
RAGFlow is a Retrieval-Augmented Generation (RAG) engine that integrates AI agents for enhanced context management in LLM applications, built using Go language and released under the Apache-2.0 license.

Persona

kotaemon
-
ragflow
-

Runtime

kotaemon
-
ragflow
-

License

kotaemon
Apache-2.0
ragflow
Apache-2.0 License

Last pushed

kotaemon
Jul 14, 2026
ragflow
Jul 31, 2026

Categories

kotaemon
Data & Retrieval, Developer Tools
ragflow
AI Agents, Data & Retrieval

Trust and health

Maintenance

kotaemon
Steady (60%)
ragflow
Very active (96%)

Days since push

kotaemon
34d
ragflow
0d

Open issues (now)

kotaemon
241
ragflow
2.0k

Stars delta

kotaemon
+138 (30d)
ragflow
Unknown

Open issues delta

kotaemon
+4 (30d)
ragflow
Unknown

OSV dependency advisories

kotaemon
No lockfile (source not queried)
ragflow
Published findings

Full report

kotaemon
Trust report
ragflow
Trust report

Typed relationship

kotaemon alternative ragflowBoth kotaemon and ragflow are RAG-based tools focused on interacting with documents using AI, making them alternatives in the chatbot/document interaction space.

Choose kotaemon if…

  • kotaemon is primarily Python; ragflow is Go.
  • Both kotaemon and ragflow are RAG-based tools focused on interacting with documents using AI, making them alternatives in the chatbot/document interaction space.
  • Tags unique to kotaemon: chatbot, llms, open-source.
  • Also covers Developer Tools.
  • When you need to customize the file types you can process beyond PDFs, HTML, MHTML, and XLSX by opting for the `full` Docker version which includes additional packages from 'unstructured'.

When NOT to use kotaemon

  • If you only need to process a limited set of file types (PDF, HTML, MHTML, XLSX) and prefer the smaller Docker image size, as the `lite` version lacks additional package dependencies.
  • In environments with strict constraints on external dependencies where installing Docker or Python packages is not feasible.
GitHubDetails

Choose ragflow if…

  • ragflow is primarily Go; kotaemon is Python.
  • Requirements: Requires Docker; Docker image size is approximately 2 GB; build process requires access to external LLM and embedding services..
  • Both kotaemon and ragflow are RAG-based tools focused on interacting with documents using AI, making them alternatives in the chatbot/document interaction space.
  • Tags unique to ragflow: agentic-ai, context management, retrieval-augmented-generation.
  • Also covers AI Agents.
  • - You need an integrated RAG system with AI agent capabilities for better context management in your applications.

When NOT to use ragflow

  • - If you specifically require a non-Golang developed RAG engine, as RAGFlow is built entirely in Go.
  • - Your setup does not support or need Docker (RAGFlow requires building a Docker image that is approximately 2 GB).
  • - You cannot use external LLM services and embedding services, as RAGFlow relies on them to function.
GitHubDetails

Explore

kotaemon trust report →ragflow trust report →Data & Retrieval category →Developer Tools category →AI Agents category →All comparisonsStack workflowsTrending tools

Sources

Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.

GitHub stars on cards: kotaemon 26k · ragflow 87k (synced Aug 18, 2026).

Common questions

What is the difference between kotaemon and ragflow?
kotaemon: An open-source RAG-based tool for chatting with your documents.. ragflow: Retrieval-Augmented Generation engine with agent capabilities. See the comparison table for live GitHub stats and shared categories.
When should I choose kotaemon over ragflow?
Choose kotaemon over ragflow when kotaemon is primarily Python; ragflow is Go; Both kotaemon and ragflow are RAG-based tools focused on interacting with documents using AI, making them alternatives in the chatbot/document interaction space; Tags unique to kotaemon: chatbot, llms, open-source; Also covers Developer Tools; When you need to customize the file types you can process beyond PDFs, HTML, MHTML, and XLSX by opting for the full Docker version which includes additional packages from 'unstructured'.
When should I choose ragflow over kotaemon?
Choose ragflow over kotaemon when ragflow is primarily Go; kotaemon is Python; Requirements: Requires Docker; Docker image size is approximately 2 GB; build process requires access to external LLM and embedding services.; Both kotaemon and ragflow are RAG-based tools focused on interacting with documents using AI, making them alternatives in the chatbot/document interaction space; Tags unique to ragflow: agentic-ai, context management, retrieval-augmented-generation; Also covers AI Agents; - You need an integrated RAG system with AI agent capabilities for better context management in your applications.
When should I avoid kotaemon?
If you only need to process a limited set of file types (PDF, HTML, MHTML, XLSX) and prefer the smaller Docker image size, as the lite version lacks additional package dependencies. In environments with strict constraints on external dependencies where installing Docker or Python packages is not feasible.
When should I avoid ragflow?
- If you specifically require a non-Golang developed RAG engine, as RAGFlow is built entirely in Go. - Your setup does not support or need Docker (RAGFlow requires building a Docker image that is approximately 2 GB). - You cannot use external LLM services and embedding services, as RAGFlow relies on them to function.
Is kotaemon or ragflow more popular on GitHub?
ragflow has more GitHub stars (86,541 vs 25,701). Stars measure visibility, not whether either tool fits your constraints.
Are kotaemon and ragflow open source?
Yes - both are open-source projects on GitHub (kotaemon: Apache-2.0, ragflow: Apache-2.0).
Where can I find alternatives to kotaemon or ragflow?
GraphCanon lists graph-backed alternatives at kotaemon alternatives and ragflow alternatives (kotaemon markdown twin, ragflow 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, kotaemon or ragflow?
kotaemon: Steady. ragflow: 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 kotaemon and ragflow?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: kotaemon trust report; ragflow trust report.

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