Comparison
RAGLight vs UltraRAG
Verdict
Pick RAGLight if rAGLight emerges as an adaptable framework for Retrieval-Augmented Generation, offering integration flexibility with multiple LLMs and external tools through MCP; pick UltraRAG if ultraRAG is a low-code framework for building retrieval-augmented generation pipelines with Python.
Markdown twin · RAGLight alternatives · UltraRAG alternatives
GraphCanon updated today
vs
Trust & integrity
| Signal | RAGLight | UltraRAG |
|---|---|---|
| Maintenance | Steady (57d since push) As of today · github_public_v1 | Very active (1d since push) As of 3d · github_public_v1 |
| Provenance | Not a fork · Personal account As of today · github_public_v1 | Not a fork · Organization account As of 3d · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) 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
- RAGLight
- A modular framework for Retrieval-Augmented Generation that supports integration with various LLMs and external tools.
- UltraRAG
- A Low-Code MCP Framework for Building Complex and Innovative RAG Pipelines
Stars
- RAGLight
- 670
- UltraRAG
- 5.7k
Forks
- RAGLight
- 101
- UltraRAG
- 437
Open issues
- RAGLight
- 12
- UltraRAG
- 18
Language
- RAGLight
- Python
- UltraRAG
- Python
Adopt for
- RAGLight
- RAGLight emerges as an adaptable framework for Retrieval-Augmented Generation, offering integration flexibility with multiple LLMs and external tools through MCP.
- UltraRAG
- UltraRAG is a low-code framework for building retrieval-augmented generation pipelines with Python.
Persona
- RAGLight
- -
- UltraRAG
- -
Runtime
- RAGLight
- -
- UltraRAG
- -
License
- RAGLight
- MIT
- UltraRAG
- Apache-2.0 license provides freedom with conditions for use, modification, and distribution.
Last pushed
- RAGLight
- Jun 25, 2026
- UltraRAG
- Aug 17, 2026
Categories
- RAGLight
- AI Agents, Data & Retrieval
- UltraRAG
- Data & Retrieval, LLM Frameworks
Trust and health
Maintenance
- RAGLight
- Steady (60%)
- UltraRAG
- Very active (96%)
Days since push
- RAGLight
- 57d
- UltraRAG
- 1d
Open issues (now)
- RAGLight
- 12
- UltraRAG
- 18
Stars delta
- RAGLight
- 0 (30d)
- UltraRAG
- +18 (30d)
Open issues delta
- RAGLight
- 0 (30d)
- UltraRAG
- -7 (30d)
Owner type
- RAGLight
- User
- UltraRAG
- Organization
Full report
- RAGLight
- Trust report
- UltraRAG
- Trust report
Choose RAGLight if…
- License: RAGLight is MIT, UltraRAG is Apache-2.0.
- Tags unique to RAGLight: agentic-ai, data-science, framework, huggingface.
- Also covers AI Agents.
- When you require seamless integration with various Language Models (LLMs) like Hugging Face or OpenAI models, making RAGLight a suitable choice for diverse model environments.
When NOT to use RAGLight
- Avoid using RAGLight if your workflow strictly demands proprietary integration methods that are not supported by its modular framework structure.
- If the project focuses on a specific LLM without the need for flexibility or interchangeability, the overhead of configuring diverse integrations in RAGLight might be unnecessary.
Choose UltraRAG if…
- License: UltraRAG is Apache-2.0, RAGLight is MIT.
- Tags unique to UltraRAG: deepseek, demo, easy, embedding.
- Also covers LLM Frameworks.
- UltraRAG ships Docker support for self-hosted deployment.
- 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 (Bessouat40/RAGLight) · observed Aug 22, 2026
- GitHub forks (Bessouat40/RAGLight) · observed Aug 22, 2026
- Last push (Bessouat40/RAGLight) · observed Jun 25, 2026
- License file (MIT) · observed Aug 22, 2026
- Decision facts (enrichment) · observed Jul 14, 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: RAGLight 670 · UltraRAG 5.7k (synced Aug 22, 2026).
Common questions
- What is the difference between RAGLight and UltraRAG?
- RAGLight: A modular framework for Retrieval-Augmented Generation that supports integration with various LLMs and external tools.. 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 RAGLight over UltraRAG?
- Choose RAGLight over UltraRAG when License: RAGLight is MIT, UltraRAG is Apache-2.0; Tags unique to RAGLight: agentic-ai, data-science, framework, huggingface; Also covers AI Agents; When you require seamless integration with various Language Models (LLMs) like Hugging Face or OpenAI models, making RAGLight a suitable choice for diverse model environments.
- When should I choose UltraRAG over RAGLight?
- Choose UltraRAG over RAGLight when License: UltraRAG is Apache-2.0, RAGLight is MIT; Tags unique to UltraRAG: deepseek, demo, easy, embedding; Also covers LLM Frameworks; UltraRAG ships Docker support for self-hosted deployment; You require a straightforward setup with uv package manager or Docker support.
- When should I avoid RAGLight?
- Avoid using RAGLight if your workflow strictly demands proprietary integration methods that are not supported by its modular framework structure. If the project focuses on a specific LLM without the need for flexibility or interchangeability, the overhead of configuring diverse integrations in RAGLight might be unnecessary.
- 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 RAGLight or UltraRAG more popular on GitHub?
- UltraRAG has more GitHub stars (5,670 vs 670). Stars measure visibility, not whether either tool fits your constraints.
- Are RAGLight and UltraRAG open source?
- Yes - both are open-source projects on GitHub (RAGLight: MIT, UltraRAG: Apache-2.0).
- Where can I find alternatives to RAGLight or UltraRAG?
- GraphCanon lists graph-backed alternatives at RAGLight alternatives and UltraRAG alternatives (RAGLight 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, RAGLight or UltraRAG?
- RAGLight: Steady. 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 RAGLight and UltraRAG?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: RAGLight trust report; UltraRAG trust report.