Comparison
ragflow vs UltraRAG
Verdict
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; pick UltraRAG if ultraRAG is a low-code framework for building retrieval-augmented generation pipelines with Python.
Markdown twin · ragflow alternatives · UltraRAG alternatives
GraphCanon updated 2d
vs
Trust & integrity
| Signal | ragflow | UltraRAG |
|---|---|---|
| Maintenance | Very active (0d since push) As of 2w · github_public_v1 | Very active (1d since push) As of 2d · github_public_v1 |
| Provenance | Not a fork · Organization account As of 2w · github_public_v1 | Not a fork · Organization account As of 2d · github_public_v1 |
| OSV dependency advisories | Published findings As of 1mo · osv@v1 | No lockfile (source not queried) 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 |
Tagline
- ragflow
- Retrieval-Augmented Generation engine with agent capabilities
- UltraRAG
- A Low-Code MCP Framework for Building Complex and Innovative RAG Pipelines
Stars
- ragflow
- 87k
- UltraRAG
- 5.7k
Forks
- ragflow
- 10k
- UltraRAG
- 437
Open issues
- ragflow
- 2.0k
- UltraRAG
- 18
Language
- ragflow
- Go
- UltraRAG
- Python
Adopt for
- 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.
- UltraRAG
- UltraRAG is a low-code framework for building retrieval-augmented generation pipelines with Python.
Persona
- ragflow
- -
- UltraRAG
- -
Runtime
- ragflow
- -
- UltraRAG
- -
License
- ragflow
- Apache-2.0 License
- UltraRAG
- Apache-2.0 license provides freedom with conditions for use, modification, and distribution.
Last pushed
- ragflow
- Jul 31, 2026
- UltraRAG
- Aug 17, 2026
Categories
- ragflow
- AI Agents, Data & Retrieval
- UltraRAG
- Data & Retrieval, LLM Frameworks
Trust and health
Days since push
- ragflow
- 0d
- UltraRAG
- 1d
Open issues (now)
- ragflow
- 2.0k
- UltraRAG
- 18
Stars delta
- ragflow
- Unknown
- UltraRAG
- +18 (30d)
Open issues delta
- ragflow
- Unknown
- UltraRAG
- -7 (30d)
OSV dependency advisories
- ragflow
- Published findings
- UltraRAG
- No lockfile (source not queried)
Full report
- ragflow
- Trust report
- UltraRAG
- Trust report
Typed relationship
ragflow alternative UltraRAGBoth UltraRAG and ragflow are systems focusing on Retrieval-Augmented Generation (RAG), providing frameworks for building efficient RAG pipelines. The main difference is in their specific implementation details and intended ease of use.
Choose ragflow if…
- ragflow is primarily Go; UltraRAG is Python.
- Requirements: Requires Docker; Docker image size is approximately 2 GB; build process requires access to external LLM and embedding services..
- Both UltraRAG and ragflow are systems focusing on Retrieval-Augmented Generation (RAG), providing frameworks for building efficient RAG pipelines. The main difference is in their specific implementation details and intended ease of use.
- Tags unique to ragflow: agentic-ai, context management, rag, 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.
Choose UltraRAG if…
- UltraRAG is primarily Python; ragflow is Go.
- Both UltraRAG and ragflow are systems focusing on Retrieval-Augmented Generation (RAG), providing frameworks for building efficient RAG pipelines. The main difference is in their specific implementation details and intended ease of use.
- Tags unique to UltraRAG: deepseek, demo, easy, embedding.
- Also covers LLM Frameworks.
- You require a straightforward setup with uv package manager or Docker support
When NOT to use UltraRAG
- Prefer tools that do not rely on specific package managers like uv
- Require more customization in pipeline creation beyond what low-code environments offer
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 Aug 1, 2026
- GitHub forks (infiniflow/ragflow) · observed Aug 1, 2026
- Last push (infiniflow/ragflow) · observed Jul 31, 2026
- License file (Apache-2.0) · observed Aug 1, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (OpenBMB/UltraRAG) · observed Aug 18, 2026
- GitHub forks (OpenBMB/UltraRAG) · observed Aug 18, 2026
- Last push (OpenBMB/UltraRAG) · observed Aug 17, 2026
- License file (Apache-2.0) · observed Aug 18, 2026
- Decision facts (enrichment) · observed Jul 14, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: ragflow 87k · UltraRAG 5.7k (synced Aug 1, 2026).
Common questions
- What is the difference between ragflow and UltraRAG?
- ragflow: Retrieval-Augmented Generation engine with agent capabilities. UltraRAG: A Low-Code MCP Framework for Building Complex and Innovative RAG Pipelines. See the comparison table for live GitHub stats and shared categories.
- When should I choose ragflow over UltraRAG?
- Choose ragflow over UltraRAG when ragflow is primarily Go; UltraRAG is Python; Requirements: Requires Docker; Docker image size is approximately 2 GB; build process requires access to external LLM and embedding services.; Both UltraRAG and ragflow are systems focusing on Retrieval-Augmented Generation (RAG), providing frameworks for building efficient RAG pipelines. The main difference is in their specific implementation details and intended ease of use; Tags unique to ragflow: agentic-ai, context management, rag, 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 choose UltraRAG over ragflow?
- Choose UltraRAG over ragflow when UltraRAG is primarily Python; ragflow is Go; Both UltraRAG and ragflow are systems focusing on Retrieval-Augmented Generation (RAG), providing frameworks for building efficient RAG pipelines. The main difference is in their specific implementation details and intended ease of use; Tags unique to UltraRAG: deepseek, demo, easy, embedding; Also covers LLM Frameworks; You require a straightforward setup with uv package manager or Docker support.
- 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.
- When should I avoid UltraRAG?
- Prefer tools that do not rely on specific package managers like uv Require more customization in pipeline creation beyond what low-code environments offer
- Is ragflow or UltraRAG more popular on GitHub?
- ragflow has more GitHub stars (86,541 vs 5,670). Stars measure visibility, not whether either tool fits your constraints.
- Are ragflow and UltraRAG open source?
- Yes - both are open-source projects on GitHub (ragflow: Apache-2.0, UltraRAG: Apache-2.0).
- Where can I find alternatives to ragflow or UltraRAG?
- GraphCanon lists graph-backed alternatives at ragflow alternatives and UltraRAG alternatives (ragflow markdown twin, UltraRAG 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 UltraRAG?
- ragflow: Very active. UltraRAG: 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 UltraRAG?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: ragflow trust report; UltraRAG trust report.