---
title: "AutoRAG vs rag-fusion"
type: "comparison"
canonical_url: "https://www.graphcanon.com/compare/marker-inc-korea-autorag-vs-raudaschl-rag-fusion"
tools: ["marker-inc-korea-autorag", "raudaschl-rag-fusion"]
---

# AutoRAG vs rag-fusion

*GraphCanon updated Jul 12, 2026*

## Verdict

Pick AutoRAG when license: AutoRAG is Apache-2.0, rag-fusion is MIT; pick rag-fusion when license: rag-fusion is MIT, AutoRAG is Apache-2.0.

[AutoRAG](https://marker-inc-korea.github.io/AutoRAG/) reports 4.9k GitHub stars, 407 forks, and 171 open issues, last pushed Jul 2, 2026. [rag-fusion](https://github.com/Raudaschl/rag-fusion) has 946 stars, 113 forks, and 0 open issues, last pushed Apr 26, 2026. Figures are from public GitHub metadata via [AutoRAG's repository](https://github.com/Marker-Inc-Korea/AutoRAG) and [rag-fusion's repository](https://github.com/Raudaschl/rag-fusion).

| | [AutoRAG](/tools/marker-inc-korea-autorag.md) | [rag-fusion](/tools/raudaschl-rag-fusion.md) |
| --- | --- | --- |
| Tagline | AutoRAG: An Open-Source Framework for Retrieval-Augmented Generation (RAG) Evaluation & Optimization with AutoML-Style Automation | RAG-Fusion: multi-query generation + Reciprocal Rank Fusion for better retrieval-augmented generation. Includes evaluation harness with NFCorpus/BEIR. |
| Stars | 4,862 | 946 |
| Forks | 407 | 113 |
| Open issues | 171 | 0 |
| Language | Python | Python |
| Adopt for | - | - |
| Persona | - | - |
| Runtime | - | - |
| License | Apache-2.0 | MIT |
| Categories | Vector Databases, LLM Frameworks, Data & Retrieval | LLM Frameworks, Data & Retrieval, Vector Databases |

## Trust and health

_Sourced signals - not a safety guarantee. No winner column._

| | [AutoRAG](/tools/marker-inc-korea-autorag.md) | [rag-fusion](/tools/raudaschl-rag-fusion.md) |
| --- | --- | --- |
| Maintenance | Active (82%) | Steady (60%) |
| Days since push | 9d | 75d |
| Open issues (now) | 171 | 0 |
| Owner type | Organization | User |
| Full report | [trust report](/tools/marker-inc-korea-autorag/trust.md) | [trust report](/tools/raudaschl-rag-fusion/trust.md) |

## Choose when

### Choose AutoRAG if…

- License: AutoRAG is Apache-2.0, rag-fusion is MIT.
- Tags unique to AutoRAG: automl, evaluation, embeddings, llm.
- More GitHub stars (4.9k vs 946) - visibility, not fit.

### Choose rag-fusion if…

- License: rag-fusion is MIT, AutoRAG is Apache-2.0.
- Tags unique to rag-fusion: python, chromadb, rag, information-retrieval.
- Leaner open-issue backlog (0).

## When NOT to use AutoRAG

- Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate.
- LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.
- Data & Retrieval: Skip a heavy ingestion framework when your corpus is small and static; a script plus the embedding API is enough.

## When NOT to use rag-fusion

- LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.
- Data & Retrieval: Skip a heavy ingestion framework when your corpus is small and static; a script plus the embedding API is enough.
- Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate.

## Common questions

### What is the difference between AutoRAG and rag-fusion?

AutoRAG: AutoRAG: An Open-Source Framework for Retrieval-Augmented Generation (RAG) Evaluation & Optimization with AutoML-Style Automation. rag-fusion: RAG-Fusion: multi-query generation + Reciprocal Rank Fusion for better retrieval-augmented generation. Includes evaluation harness with NFCorpus/BEIR.. See the comparison table for live GitHub stats and shared categories.

### When should I choose AutoRAG over rag-fusion?

Choose AutoRAG over rag-fusion when License: AutoRAG is Apache-2.0, rag-fusion is MIT; Tags unique to AutoRAG: automl, evaluation, embeddings, llm; More GitHub stars (4.9k vs 946) - visibility, not fit.

### When should I choose rag-fusion over AutoRAG?

Choose rag-fusion over AutoRAG when License: rag-fusion is MIT, AutoRAG is Apache-2.0; Tags unique to rag-fusion: python, chromadb, rag, information-retrieval; Leaner open-issue backlog (0).

### When should I avoid AutoRAG?

Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. Data & Retrieval: Skip a heavy ingestion framework when your corpus is small and static; a script plus the embedding API is enough.

### When should I avoid rag-fusion?

LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. Data & Retrieval: Skip a heavy ingestion framework when your corpus is small and static; a script plus the embedding API is enough. Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate.

### Is AutoRAG or rag-fusion more popular on GitHub?

AutoRAG has more GitHub stars (4,862 vs 946). Stars measure visibility, not whether either tool fits your constraints.

### Are AutoRAG and rag-fusion open source?

Yes - both are open-source projects on GitHub (AutoRAG: Apache-2.0, rag-fusion: MIT).

### Where can I find alternatives to AutoRAG or rag-fusion?

GraphCanon lists graph-backed alternatives at [AutoRAG alternatives](/tools/marker-inc-korea-autorag/alternatives) and [rag-fusion alternatives](/tools/raudaschl-rag-fusion/alternatives) ([AutoRAG markdown twin](/tools/marker-inc-korea-autorag/alternatives.md), [rag-fusion markdown twin](/tools/raudaschl-rag-fusion/alternatives.md)), 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](/compare/marker-inc-korea-autorag-vs-raudaschl-rag-fusion.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.

### Which is better maintained, AutoRAG or rag-fusion?

AutoRAG: Active. rag-fusion: Steady. 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 AutoRAG and rag-fusion?

GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [AutoRAG trust report](/tools/marker-inc-korea-autorag/trust); [rag-fusion trust report](/tools/raudaschl-rag-fusion/trust).

---

**Machine-readable endpoints**

- JSON: [`/api/graphcanon/graph?tool=marker-inc-korea-autorag`](/api/graphcanon/graph?tool=marker-inc-korea-autorag)
- LLM index: [/llms.txt](/llms.txt)
- Full corpus: [/llms-full.txt](/llms-full.txt)

_GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_