Comparison
DB-GPT vs ragflow
Verdict
Pick DB-GPT if dB-GPT is an open-source framework that integrates with various LLM services, streamlining tasks from reasoning to SQL execution and planning; 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.
Markdown twin · DB-GPT alternatives · ragflow alternatives
GraphCanon updated Sep 20, 2026
15views this month
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Trust & integrity
| Signal | DB-GPT | ragflow |
|---|---|---|
| Maintenance | Very active (0d since push) As of Aug 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 Aug 18, 2026 · github_public_v1 | Not a fork · Organization account As of Sep 18, 2026 · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of Jul 11, 2026 · osv@v1 | Published findings 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
- DB-GPT
- open-source agentic AI data assistant for the next generation of AI + Data products
- ragflow
- Retrieval-Augmented Generation (RAG) engine with agent capabilities
Stars
- DB-GPT
- 20k
- ragflow
- 91k
Forks
- DB-GPT
- 2.9k
- ragflow
- 11k
Open issues
- DB-GPT
- 428
- ragflow
- 1.4k
Language
- DB-GPT
- Python
- ragflow
- Go
Adopt for
- DB-GPT
- DB-GPT is an open-source framework that integrates with various LLM services, streamlining tasks from reasoning to SQL execution and planning.
- 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.
Persona
- DB-GPT
- -
- ragflow
- -
Runtime
- DB-GPT
- -
- ragflow
- -
License
- DB-GPT
- MIT
- ragflow
- Apache-2.0
Last pushed
- DB-GPT
- Aug 17, 2026
- ragflow
- Sep 18, 2026
Categories
- DB-GPT
- Data & Retrieval, LLM Frameworks
- ragflow
- AI Agents, Data & Retrieval
Trust and health
Open issues (now)
- DB-GPT
- 428
- ragflow
- 1.4k
Stars delta
- DB-GPT
- +239 (30d)
- ragflow
- +4.4k (30d)
Open issues delta
- DB-GPT
- -5 (30d)
- ragflow
- -553 (30d)
OSV dependency advisories
- DB-GPT
- No lockfile (source not queried)
- ragflow
- Published findings
Full report
- DB-GPT
- Trust report
- ragflow
- Trust report
Typed relationship
DB-GPT alternative ragflowRAGFlow and DB-GPT both deal with retrieval-augmented generation (RAG), integrating agent capabilities with context management, albeit possibly in different ways.
Choose DB-GPT if…
- DB-GPT is primarily Python; ragflow is Go.
- License: DB-GPT is MIT, ragflow is Apache-2.0.
- RAGFlow and DB-GPT both deal with retrieval-augmented generation (RAG), integrating agent capabilities with context management, albeit possibly in different ways.
- Tags unique to DB-GPT: agents, bgi, database, deepseek.
- Also covers LLM Frameworks.
- - You need a tool that can handle complex data processing and task automation using AI.
When NOT to use DB-GPT
- - You are looking for a heavily community-customized or fine-tuned experience as,DB-GPT's flexibility might be limited compared to more customizable systems.
- - Your use case strictly requires proprietary services and you seek a tool without dependency on third-party LLM services which DB-GPT inherently relies upon.
- - Deployment contexts that strictly adhere to closed-source frameworks or environments where open-source software is restricted might not align well with DB-GPT’s licensing model.
Choose ragflow if…
- ragflow is primarily Go; DB-GPT is Python.
- License: ragflow is Apache-2.0, DB-GPT is MIT.
- RAGFlow and DB-GPT both deal with retrieval-augmented generation (RAG), integrating agent capabilities with context management, albeit possibly in different ways.
- Tags unique to ragflow: agent-harness, agentic-ai, agentic-retrieval, agentic-search.
- Also covers AI Agents.
- 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.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (eosphoros-ai/DB-GPT) · observed Sep 20, 2026
- GitHub forks (eosphoros-ai/DB-GPT) · observed Sep 20, 2026
- Last push (eosphoros-ai/DB-GPT) · observed Aug 17, 2026
- License file (MIT) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- 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 on cards: DB-GPT 20k · ragflow 91k (synced Sep 20, 2026).
Common questions
- What is the difference between DB-GPT and ragflow?
- DB-GPT: open-source agentic AI data assistant for the next generation of AI + Data products. ragflow: Retrieval-Augmented Generation (RAG) engine with agent capabilities. See the comparison table for live GitHub stats and shared categories.
- When should I choose DB-GPT over ragflow?
- Choose DB-GPT over ragflow when DB-GPT is primarily Python; ragflow is Go; License: DB-GPT is MIT, ragflow is Apache-2.0; RAGFlow and DB-GPT both deal with retrieval-augmented generation (RAG), integrating agent capabilities with context management, albeit possibly in different ways; Tags unique to DB-GPT: agents, bgi, database, deepseek; Also covers LLM Frameworks; - You need a tool that can handle complex data processing and task automation using AI.
- When should I choose ragflow over DB-GPT?
- Choose ragflow over DB-GPT when ragflow is primarily Go; DB-GPT is Python; License: ragflow is Apache-2.0, DB-GPT is MIT; RAGFlow and DB-GPT both deal with retrieval-augmented generation (RAG), integrating agent capabilities with context management, albeit possibly in different ways; Tags unique to ragflow: agent-harness, agentic-ai, agentic-retrieval, agentic-search; Also covers AI Agents; When you need an open-source RAG engine that can integrate with external LLM and embedding services to enhance context management.
- When should I avoid DB-GPT?
- - You are looking for a heavily community-customized or fine-tuned experience as,DB-GPT's flexibility might be limited compared to more customizable systems. - Your use case strictly requires proprietary services and you seek a tool without dependency on third-party LLM services which DB-GPT inherently relies upon. - Deployment contexts that strictly adhere to closed-source frameworks or environments where open-source software is restricted might not align well with DB-GPT’s licensing model.
- 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.
- Is DB-GPT or ragflow more popular on GitHub?
- ragflow has more GitHub stars (90,923 vs 19,740). Stars measure visibility, not whether either tool fits your constraints.
- Are DB-GPT and ragflow open source?
- Yes - both are open-source projects on GitHub (DB-GPT: MIT, ragflow: Apache-2.0).
- Where can I find alternatives to DB-GPT or ragflow?
- GraphCanon lists graph-backed alternatives at DB-GPT alternatives and ragflow alternatives (DB-GPT 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, DB-GPT or ragflow?
- DB-GPT: Very active. 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 DB-GPT and ragflow?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: DB-GPT trust report; ragflow trust report.