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 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 · DB-GPT alternatives · ragflow alternatives
GraphCanon updated 3d
vs
Trust & integrity
| Signal | DB-GPT | ragflow |
|---|---|---|
| Maintenance | Very active (0d since push) As of 3d · github_public_v1 | Very active (0d since push) As of 2w · github_public_v1 |
| Provenance | Not a fork · Organization account As of 3d · github_public_v1 | Not a fork · Organization account As of 2w · 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 |
Tagline
- DB-GPT
- open-source agentic AI data assistant for the next generation of AI + Data products
- ragflow
- Retrieval-Augmented Generation engine with agent capabilities
Stars
- DB-GPT
- 20k
- ragflow
- 87k
Forks
- DB-GPT
- 2.9k
- ragflow
- 10k
Open issues
- DB-GPT
- 428
- ragflow
- 2.0k
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 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
- DB-GPT
- -
- ragflow
- -
Runtime
- DB-GPT
- -
- ragflow
- -
License
- DB-GPT
- MIT
- ragflow
- Apache-2.0 License
Last pushed
- DB-GPT
- Aug 17, 2026
- ragflow
- Jul 31, 2026
Categories
- DB-GPT
- Data & Retrieval, LLM Frameworks
- ragflow
- AI Agents, Data & Retrieval
Trust and health
Open issues (now)
- DB-GPT
- 428
- ragflow
- 2.0k
Stars delta
- DB-GPT
- +239 (30d)
- ragflow
- Unknown
Open issues delta
- DB-GPT
- -5 (30d)
- ragflow
- Unknown
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.
- Requirements: Requires Docker; Docker image size is approximately 2 GB; build process requires access to external LLM and embedding services..
- 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: 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.
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 Aug 18, 2026
- GitHub forks (eosphoros-ai/DB-GPT) · observed Aug 18, 2026
- Last push (eosphoros-ai/DB-GPT) · observed Aug 17, 2026
- License file (MIT) · observed Aug 18, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- 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 on cards: DB-GPT 20k · ragflow 87k (synced Aug 18, 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 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; Requirements: Requires Docker; Docker image size is approximately 2 GB; build process requires access to external LLM and embedding services.; 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: 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 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 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 DB-GPT or ragflow more popular on GitHub?
- ragflow has more GitHub stars (86,541 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.