Comparison
DB-GPT-Hub vs awesome
Verdict
Pick DB-GPT-Hub when license: DB-GPT-Hub is MIT, awesome is CC0-1.0; pick awesome when license: awesome is CC0-1.0, DB-GPT-Hub is MIT.
Markdown twin · DB-GPT-Hub alternatives · awesome alternatives
GraphCanon updated today
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Trust & integrity
| Signal | DB-GPT-Hub | awesome |
|---|---|---|
| Maintenance | Dormant (374d since push) As of today · github_public_v1 | Active (11d 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 |
Tagline
- DB-GPT-Hub
- A repository that contains models, datasets, and fine-tuning techniques for DB-GPT, with the purpose of enhancing model performance in Text-to-SQL
- awesome
- 😎 Curated list of awesome topics including hardware resources
Stars
- DB-GPT-Hub
- 2.0k
- awesome
- 484k
Forks
- DB-GPT-Hub
- 250
- awesome
- 36k
Open issues
- DB-GPT-Hub
- 73
- awesome
- 92
Language
- DB-GPT-Hub
- Python
- awesome
- -
Adopt for
- DB-GPT-Hub
- -
- awesome
- -
Persona
- DB-GPT-Hub
- -
- awesome
- -
Runtime
- DB-GPT-Hub
- -
- awesome
- -
License
- DB-GPT-Hub
- MIT
- awesome
- CC0-1.0
Last pushed
- DB-GPT-Hub
- Jul 2, 2025
- awesome
- Jun 30, 2026
Categories
- DB-GPT-Hub
- LLM Frameworks
- awesome
- LLM Frameworks
Trust and health
Maintenance
- DB-GPT-Hub
- Dormant (18%)
- awesome
- Active (82%)
Days since push
- DB-GPT-Hub
- 374d
- awesome
- 11d
Open issues (now)
- DB-GPT-Hub
- 73
- awesome
- 92
Owner type
- DB-GPT-Hub
- Organization
- awesome
- User
Full report
- DB-GPT-Hub
- Trust report
- awesome
- Trust report
Choose DB-GPT-Hub if…
- License: DB-GPT-Hub is MIT, awesome is CC0-1.0.
- Tags unique to DB-GPT-Hub: fine-tuning, llm, datasets, hacktoberfest.
- Leaner open-issue backlog (73).
When NOT to use DB-GPT-Hub
- Last GitHub push was 375 days ago (dormant maintenance, Jul 2, 2025). Validate activity before betting a new project on DB-GPT-Hub.
- LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.
Choose awesome if…
- License: awesome is CC0-1.0, DB-GPT-Hub is MIT.
- Tags unique to awesome: resources, awesome-list.
- More GitHub stars (484k vs 2.0k) - visibility, not fit.
When NOT to use awesome
- LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.
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-Hub) · observed Jul 11, 2026
- GitHub forks (eosphoros-ai/DB-GPT-Hub) · observed Jul 11, 2026
- Last push (eosphoros-ai/DB-GPT-Hub) · observed Jul 2, 2025
- License file (MIT) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (sindresorhus/awesome) · observed Jul 11, 2026
- GitHub forks (sindresorhus/awesome) · observed Jul 11, 2026
- Last push (sindresorhus/awesome) · observed Jun 30, 2026
- License file (CC0-1.0) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: DB-GPT-Hub 2.0k · awesome 484k (synced Jul 11, 2026).
Common questions
- What is the difference between DB-GPT-Hub and awesome?
- DB-GPT-Hub: A repository that contains models, datasets, and fine-tuning techniques for DB-GPT, with the purpose of enhancing model performance in Text-to-SQL. awesome: 😎 Curated list of awesome topics including hardware resources. See the comparison table for live GitHub stats and shared categories.
- When should I choose DB-GPT-Hub over awesome?
- Choose DB-GPT-Hub over awesome when License: DB-GPT-Hub is MIT, awesome is CC0-1.0; Tags unique to DB-GPT-Hub: fine-tuning, llm, datasets, hacktoberfest; Leaner open-issue backlog (73).
- When should I choose awesome over DB-GPT-Hub?
- Choose awesome over DB-GPT-Hub when License: awesome is CC0-1.0, DB-GPT-Hub is MIT; Tags unique to awesome: resources, awesome-list; More GitHub stars (484k vs 2.0k) - visibility, not fit.
- When should I avoid DB-GPT-Hub?
- Last GitHub push was 375 days ago (dormant maintenance, Jul 2, 2025). Validate activity before betting a new project on DB-GPT-Hub. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.
- When should I avoid awesome?
- LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.
- Is DB-GPT-Hub or awesome more popular on GitHub?
- awesome has more GitHub stars (484,026 vs 1,997). Stars measure visibility, not whether either tool fits your constraints.
- Are DB-GPT-Hub and awesome open source?
- Yes - both are open-source projects on GitHub (DB-GPT-Hub: MIT, awesome: CC0-1.0).
- Where can I find alternatives to DB-GPT-Hub or awesome?
- GraphCanon lists graph-backed alternatives at DB-GPT-Hub alternatives and awesome alternatives (DB-GPT-Hub markdown twin, awesome 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-Hub or awesome?
- DB-GPT-Hub: Dormant. awesome: 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-Hub and awesome?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: DB-GPT-Hub trust report; awesome trust report.