Comparison
rags vs docetl
Verdict
Pick rags if decision-critical facts for 'rags':; pick docetl if docetl is an agentic system that employs large language models for data processing and ETL operations, specifically suited to handle unstructured document analysis tasks.
Markdown twin · rags alternatives · docetl alternatives
GraphCanon updated Sep 20, 2026
14views this month
Trust & integrity
| Signal | rags | docetl |
|---|---|---|
| Maintenance | Dormant (865d since push) As of Aug 18, 2026 · github_public_v1 | Active (9d since push) As of Sep 15, 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 15, 2026 · github_public_v1 |
| OSV dependency advisories | Published findings As of Jul 11, 2026 · osv@v1 | No lockfile (source not queried) As of Jul 15, 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
- rags
- Build ChatGPT over your data with natural language
- docetl
- A system for agentic LLM-powered data processing and ETL
Stars
- rags
- 6.5k
- docetl
- 4.1k
Forks
- rags
- 656
- docetl
- 443
Open issues
- rags
- 37
- docetl
- 45
Language
- rags
- Python
- docetl
- Python
Adopt for
- rags
- Decision-critical facts for 'rags':
- docetl
- Docetl is an agentic system that employs large language models for data processing and ETL operations, specifically suited to handle unstructured document analysis tasks.
Persona
- rags
- -
- docetl
- -
Runtime
- rags
- -
- docetl
- -
License
- rags
- MIT License
- docetl
- MIT
Last pushed
- rags
- Apr 5, 2024
- docetl
- Sep 5, 2026
Categories
- rags
- AI Agents, Data & Retrieval
- docetl
- AI Agents, Data & Retrieval
Trust and health
Maintenance
- rags
- Dormant (18%)
- docetl
- Active (82%)
Days since push
- rags
- 865d
- docetl
- 9d
Open issues (now)
- rags
- 37
- docetl
- 45
Stars delta
- rags
- +6 (30d)
- docetl
- +131 (30d)
Open issues delta
- rags
- -1 (30d)
- docetl
- +3 (30d)
OSV dependency advisories
- rags
- Published findings
- docetl
- No lockfile (source not queried)
Full report
- rags
- Trust report
- docetl
- Trust report
Shared compatibility
- Python · rags: Python runtime · docetl: Python runtime
Choose rags if…
- Requirements: Installation leverages poetry for dependency management.; Setup requires configuration with OpenAI key and potentially creating a virtual environment..
- Tags unique to rags: agent, chatbot, chatgpt, openai.
- When leveraging natural language queries over proprietary user data using OpenAI services.
When NOT to use rags
- Not suitable if you seek solutions not dependent on OpenAI's services as the underlying framework is tightly coupled with OpenAI APIs.
- Avoid using rags if your project involves sensitive or highly confidential data since it requires integrating API keys, potentially posing security concerns.
- If your team does not have familiarity or access to Streamlit for app development, you might find setting up and deploying a conversational agent more challenging.
Choose docetl if…
- Tags unique to docetl: agents, data, document-analysis, etl.
- docetl ships Docker support for self-hosted deployment.
- When you require integration with any LLM provider through API keys like OPENAI_API_KEY.
When NOT to use docetl
- If your project strictly requires low-latency processing for real-time applications, as Docetl's agentic approach might introduce higher latency due to backend API calls.
- In scenarios where the document datasets are predominantly structured or semi-structured, making traditional ETL tools more efficient.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (run-llama/rags) · observed Sep 20, 2026
- GitHub forks (run-llama/rags) · observed Sep 20, 2026
- Last push (run-llama/rags) · observed Apr 5, 2024
- License file (MIT) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 12, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (ucbepic/docetl) · observed Sep 20, 2026
- GitHub forks (ucbepic/docetl) · observed Sep 20, 2026
- Last push (ucbepic/docetl) · observed Sep 5, 2026
- License file (MIT) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 16, 2026
- Trust scan (lockfile / OSV) · observed Jul 15, 2026
GitHub stars on cards: rags 6.5k · docetl 4.1k (synced Sep 20, 2026).
Common questions
- What is the difference between rags and docetl?
- rags: Build ChatGPT over your data with natural language. docetl: A system for agentic LLM-powered data processing and ETL. See the comparison table for live GitHub stats and shared categories.
- When should I choose rags over docetl?
- Choose rags over docetl when Requirements: Installation leverages poetry for dependency management.; Setup requires configuration with OpenAI key and potentially creating a virtual environment.; Tags unique to rags: agent, chatbot, chatgpt, openai; When leveraging natural language queries over proprietary user data using OpenAI services.
- When should I choose docetl over rags?
- Choose docetl over rags when Tags unique to docetl: agents, data, document-analysis, etl; docetl ships Docker support for self-hosted deployment; When you require integration with any LLM provider through API keys like OPENAI_API_KEY.
- When should I avoid rags?
- Not suitable if you seek solutions not dependent on OpenAI's services as the underlying framework is tightly coupled with OpenAI APIs. Avoid using rags if your project involves sensitive or highly confidential data since it requires integrating API keys, potentially posing security concerns. If your team does not have familiarity or access to Streamlit for app development, you might find setting up and deploying a conversational agent more challenging.
- When should I avoid docetl?
- If your project strictly requires low-latency processing for real-time applications, as Docetl's agentic approach might introduce higher latency due to backend API calls. In scenarios where the document datasets are predominantly structured or semi-structured, making traditional ETL tools more efficient.
- Is rags or docetl more popular on GitHub?
- rags has more GitHub stars (6,549 vs 4,092). Stars measure visibility, not whether either tool fits your constraints.
- Are rags and docetl open source?
- Yes - both are open-source projects on GitHub (rags: MIT, docetl: MIT).
- Where can I find alternatives to rags or docetl?
- GraphCanon lists graph-backed alternatives at rags alternatives and docetl alternatives (rags markdown twin, docetl 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, rags or docetl?
- rags: Dormant. docetl: 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 rags and docetl?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: rags trust report; docetl trust report.