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Home/Compare/AutoRAG vs rag-fusion

Comparison

AutoRAG vs rag-fusion

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.

Markdown twin · AutoRAG alternatives · rag-fusion alternatives

GraphCanon updated today

AutoRAG logo

AutoRAG

Marker-Inc-Korea/AutoRAG

★ 4.9kpushed Jul 2, 2026
vs
rag-fusion logo

rag-fusion

Raudaschl/rag-fusion

★ 946pushed Apr 26, 2026

Trust & integrity

SignalAutoRAGrag-fusion
Maintenance
Active (9d since push)
As of today · github_public_v1
Steady (75d since push)
As of today · github_public_v1
Provenance
Not a fork · Organization account
As of today · github_public_v1
Not a fork · Personal account
As of today · github_public_v1
Security (OSV)
No lockfile
As of today · none
No lockfile
As of today · none
AutoRAG trust reportrag-fusion trust reportTrust methodology

Tagline

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.

Stars

AutoRAG
4.9k
rag-fusion
946

Forks

AutoRAG
407
rag-fusion
113

Open issues

AutoRAG
171
rag-fusion
0

Language

AutoRAG
Python
rag-fusion
Python

Adopt for

AutoRAG
-
rag-fusion
-

Persona

AutoRAG
-
rag-fusion
-

Runtime

AutoRAG
-
rag-fusion
-

License

AutoRAG
Apache-2.0
rag-fusion
MIT

Last pushed

AutoRAG
Jul 2, 2026
rag-fusion
Apr 26, 2026

Categories

AutoRAG
Vector Databases, Data & Retrieval, LLM Frameworks
rag-fusion
Vector Databases, LLM Frameworks, Data & Retrieval

Trust and health

Maintenance

AutoRAG
Active (82%)
rag-fusion
Steady (60%)

Days since push

AutoRAG
9d
rag-fusion
75d

Open issues (now)

AutoRAG
171
rag-fusion
0

Owner type

AutoRAG
Organization
rag-fusion
User

Full report

AutoRAG
Trust report
rag-fusion
Trust report

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.

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.
  • Data & Retrieval: Skip a heavy ingestion framework when your corpus is small and static; a script plus the embedding API is enough.
  • LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.
GitHubDetails

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 rag-fusion

  • 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.
GitHubDetails

Explore

AutoRAG trust report →rag-fusion trust report →Vector Databases category →Data & Retrieval category →LLM Frameworks category →All comparisonsStack workflowsTrending tools

Sources

Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.

GitHub stars on cards: AutoRAG 4.9k · rag-fusion 946 (synced Jul 11, 2026).

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. Data & Retrieval: Skip a heavy ingestion framework when your corpus is small and static; a script plus the embedding API is enough. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.
When should I avoid rag-fusion?
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.
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 and rag-fusion alternatives (AutoRAG markdown twin, rag-fusion 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, 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; rag-fusion trust report.