Comparison
DB-GPT-Hub vs Awesome-Prompt-Engineering
Verdict
Pick DB-GPT-Hub if dB-GPT-Hub offers resources for improving DB-GPT's Text-to-SQL capabilities through fine-tuning techniques and relevant datasets; pick Awesome-Prompt-Engineering if awesome-Prompt-Engineering curates resources tailored for GPT, ChatGPT, PaLM prompt engineering in TypeScript under Apache-2.0 license.
Markdown twin · DB-GPT-Hub alternatives · Awesome-Prompt-Engineering alternatives
GraphCanon updated Sep 20, 2026
8views this month
vs
Trust & integrity
| Signal | DB-GPT-Hub | Awesome-Prompt-Engineering |
|---|---|---|
| Maintenance | Dormant (444d since push) As of Sep 19, 2026 · github_public_v1 | Very active (0d since push) As of Sep 20, 2026 · github_public_v1 |
| Provenance | Not a fork · Organization account As of Sep 19, 2026 · github_public_v1 | Not a fork · Organization account As of Sep 20, 2026 · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of Jul 11, 2026 · osv@v1 | No lockfile (source not queried) As of Jul 11, 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
- DB-GPT-Hub
- Repository for DB-GPT models, datasets, and techniques aimed at Text-to-SQL performance enhancement.
- Awesome-Prompt-Engineering
- Hand-curated resources for Prompt Engineering focusing on Generative Pre-trained Transformers
Stars
- DB-GPT-Hub
- 2.0k
- Awesome-Prompt-Engineering
- 6.3k
Forks
- DB-GPT-Hub
- 250
- Awesome-Prompt-Engineering
- 765
Open issues
- DB-GPT-Hub
- 73
- Awesome-Prompt-Engineering
- 116
Language
- DB-GPT-Hub
- Python
- Awesome-Prompt-Engineering
- TypeScript
Adopt for
- DB-GPT-Hub
- DB-GPT-Hub offers resources for improving DB-GPT's Text-to-SQL capabilities through fine-tuning techniques and relevant datasets.
- Awesome-Prompt-Engineering
- Awesome-Prompt-Engineering curates resources tailored for GPT, ChatGPT, PaLM prompt engineering in TypeScript under Apache-2.0 license.
Persona
- DB-GPT-Hub
- -
- Awesome-Prompt-Engineering
- -
Runtime
- DB-GPT-Hub
- -
- Awesome-Prompt-Engineering
- -
License
- DB-GPT-Hub
- MIT
- Awesome-Prompt-Engineering
- Apache-2.0
Last pushed
- DB-GPT-Hub
- Jul 2, 2025
- Awesome-Prompt-Engineering
- Sep 19, 2026
Categories
- DB-GPT-Hub
- LLM Frameworks, Model Training
- Awesome-Prompt-Engineering
- Developer Tools, Model Training
Trust and health
Maintenance
- DB-GPT-Hub
- Dormant (18%)
- Awesome-Prompt-Engineering
- Very active (96%)
Days since push
- DB-GPT-Hub
- 444d
- Awesome-Prompt-Engineering
- 0d
Open issues (now)
- DB-GPT-Hub
- 73
- Awesome-Prompt-Engineering
- 116
Stars delta
- DB-GPT-Hub
- +13 (30d)
- Awesome-Prompt-Engineering
- +139 (30d)
Open issues delta
- DB-GPT-Hub
- 0 (30d)
- Awesome-Prompt-Engineering
- +22 (30d)
Full report
- DB-GPT-Hub
- Trust report
- Awesome-Prompt-Engineering
- Trust report
Shared compatibility
- Python · DB-GPT-Hub: Python runtime · Awesome-Prompt-Engineering: Python runtime
Choose DB-GPT-Hub if…
- DB-GPT-Hub is primarily Python; Awesome-Prompt-Engineering is TypeScript.
- License: DB-GPT-Hub is MIT, Awesome-Prompt-Engineering is Apache-2.0.
- Tags unique to DB-GPT-Hub: database, datasets, fine-tuning, hacktoberfest.
- Also covers LLM Frameworks.
- Use when you need to improve Text-to-SQL performance specifically with the DB-GPT model, as this repository is specialized for enhancing its functionalities.
When NOT to use DB-GPT-Hub
- Avoid using when your project does not involve the DB-GPT model, as resources and techniques here are tailor-made for this specific model.
- Do not utilize if you require immediate results without the need for model customization or performance enhancement through fine-tuning.
Choose Awesome-Prompt-Engineering if…
- Awesome-Prompt-Engineering is primarily TypeScript; DB-GPT-Hub is Python.
- License: Awesome-Prompt-Engineering is Apache-2.0, DB-GPT-Hub is MIT.
- Tags unique to Awesome-Prompt-Engineering: chatgpt, deep-learning, few-shot-learning, machine-learning.
- Also covers Developer Tools.
- You need focused materials on GPT and related models for prompt engineering
When NOT to use Awesome-Prompt-Engineering
- The project requires languages other than TypeScript
- Resource is about areas outside of GPT, ChatGPT, PaLM prompt engineering
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 Sep 20, 2026
- GitHub forks (eosphoros-ai/DB-GPT-Hub) · observed Sep 20, 2026
- Last push (eosphoros-ai/DB-GPT-Hub) · observed Jul 2, 2025
- License file (MIT) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 15, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (promptslab/Awesome-Prompt-Engineering) · observed Sep 20, 2026
- GitHub forks (promptslab/Awesome-Prompt-Engineering) · observed Sep 20, 2026
- Last push (promptslab/Awesome-Prompt-Engineering) · observed Sep 19, 2026
- License file (Apache-2.0) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 16, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: DB-GPT-Hub 2.0k · Awesome-Prompt-Engineering 6.3k (synced Sep 20, 2026).
Common questions
- What is the difference between DB-GPT-Hub and Awesome-Prompt-Engineering?
- DB-GPT-Hub: Repository for DB-GPT models, datasets, and techniques aimed at Text-to-SQL performance enhancement.. Awesome-Prompt-Engineering: Hand-curated resources for Prompt Engineering focusing on Generative Pre-trained Transformers. See the comparison table for live GitHub stats and shared categories.
- When should I choose DB-GPT-Hub over Awesome-Prompt-Engineering?
- Choose DB-GPT-Hub over Awesome-Prompt-Engineering when DB-GPT-Hub is primarily Python; Awesome-Prompt-Engineering is TypeScript; License: DB-GPT-Hub is MIT, Awesome-Prompt-Engineering is Apache-2.0; Tags unique to DB-GPT-Hub: database, datasets, fine-tuning, hacktoberfest; Also covers LLM Frameworks; Use when you need to improve Text-to-SQL performance specifically with the DB-GPT model, as this repository is specialized for enhancing its functionalities.
- When should I choose Awesome-Prompt-Engineering over DB-GPT-Hub?
- Choose Awesome-Prompt-Engineering over DB-GPT-Hub when Awesome-Prompt-Engineering is primarily TypeScript; DB-GPT-Hub is Python; License: Awesome-Prompt-Engineering is Apache-2.0, DB-GPT-Hub is MIT; Tags unique to Awesome-Prompt-Engineering: chatgpt, deep-learning, few-shot-learning, machine-learning; Also covers Developer Tools; You need focused materials on GPT and related models for prompt engineering.
- When should I avoid DB-GPT-Hub?
- Avoid using when your project does not involve the DB-GPT model, as resources and techniques here are tailor-made for this specific model. Do not utilize if you require immediate results without the need for model customization or performance enhancement through fine-tuning.
- When should I avoid Awesome-Prompt-Engineering?
- The project requires languages other than TypeScript Resource is about areas outside of GPT, ChatGPT, PaLM prompt engineering
- Is DB-GPT-Hub or Awesome-Prompt-Engineering more popular on GitHub?
- Awesome-Prompt-Engineering has more GitHub stars (6,336 vs 2,014). Stars measure visibility, not whether either tool fits your constraints.
- Are DB-GPT-Hub and Awesome-Prompt-Engineering open source?
- Yes - both are open-source projects on GitHub (DB-GPT-Hub: MIT, Awesome-Prompt-Engineering: Apache-2.0).
- Where can I find alternatives to DB-GPT-Hub or Awesome-Prompt-Engineering?
- GraphCanon lists graph-backed alternatives at DB-GPT-Hub alternatives and Awesome-Prompt-Engineering alternatives (DB-GPT-Hub markdown twin, Awesome-Prompt-Engineering 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-Prompt-Engineering?
- DB-GPT-Hub: Dormant. Awesome-Prompt-Engineering: 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 DB-GPT-Hub and Awesome-Prompt-Engineering?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: DB-GPT-Hub trust report; Awesome-Prompt-Engineering trust report.