DB-GPT vs LangBot
Short answer
DB-GPT: AI data assistant that connects to your databases, writes SQL and code, and turns analysis into reports. LangBot: Platform for AI chatbots on WeChat, WeCom, QQ, Feishu, DingTalk, Slack, Discord and Telegram, run from one dashboard. Both are in our AI app & agent builders category.
Our data does not separate them on cost, hardware, license, activity or deploy method (or one of them does not publish the figure). Decide on features: read the descriptions on each app page and try both.
LangBot publishes no official RAM figure, so we cannot compare hosting cost directly.
Last updated · computed from each project's official docs and live GitHub data · sources
DB-GPT vs LangBot side by side
| DB-GPT | LangBot | |
|---|---|---|
| Category | AI app & agent builders | AI app & agent builders |
| What it is | AI data assistant that connects to your databases, writes SQL and code, and turns analysis into reports. | Platform for AI chatbots on WeChat, WeCom, QQ, Feishu, DingTalk, Slack, Discord and Telegram, run from one dashboard. |
| License | MIT | Apache-2.0 |
| License type | Permissive | Permissive |
| License conditions | Permissive. Internal and commercial use, modification and redistribution allowed; keep the copyright and license notice. | Permissive. Internal and commercial use allowed; keep license and notices. |
| Status | Active | Active |
| GitHub stars | 20.3k | 18.7k |
| Last commit | Nov 2, 2026 | Nov 4, 2026 |
| Latest release | v0.8.2 | v4.11.4 |
| Minimum hardware | 2 vCPU · 4 GB RAM · 10 GB disk | Not published |
| Recommended hardware | Not published | Not published |
| RAM measured by us | Not tested yet | Not tested yet |
| GPU | Optional. API proxy models (OpenAI, DeepSeek, Qwen, SiliconFlow) need no GPU and run on a CPU-only machine; local inference with vLLM or Hugging Face needs an NVIDIA GPU (8 GB+ VRAM for 7B models, 24 GB+ for 13B+). | Not required / not stated |
| Est. server cost | from €19.99/mo | Not estimated |
| Deploy method | Docker Compose (web server + MySQL) | Docker Compose |
| Known gotchas | 4 listed | 4 listed |
| Telemetry | Not documented | On by default |
| Calls home by default | Not documented | Yes, by default |
| SSO (OIDC / SAML / LDAP) | Not documented | Not documented |
| Audit log | Not documented | Not documented |
| RBAC | Not documented | Yes, free |
| Details | Full DB-GPT guide → | Full LangBot guide → |
Key differences
- License: DB-GPT: MIT (Permissive). LangBot: Apache-2.0 (Permissive).
- Official hardware: DB-GPT: minimum 2 vCPU · 4 GB RAM · 10 GB disk. LangBot: not published.
- GPU: DB-GPT: optional / see notes. LangBot: not required or not stated.
- Est. server cost: DB-GPT: from €19.99/mo. LangBot: not estimated (no official RAM figure).
- Deploy: DB-GPT: Docker Compose (web server + MySQL) · multi-container stack. LangBot: Docker Compose · multi-container stack.
- GitHub stars: DB-GPT: 20.3k. LangBot: 18.7k.
- Last commit: DB-GPT: Nov 2, 2026. LangBot: Nov 4, 2026.
- Latest release: DB-GPT: v0.8.2 (Aug 26, 2026). LangBot: v4.11.4 (Oct 29, 2026).
Same for both: Category: AI app & agent builders; Status: Active.
The two projects share too few published figures for a data-based recommendation. We do not fill gaps with guesses.
DB-GPT vs LangBot: FAQ
DB-GPT or LangBot: which should a small business choose?
Our data does not separate them on cost, hardware, license, activity or deploy method (or one of them does not publish the figure). Decide on features: read the descriptions on each app page and try both. LangBot publishes no official RAM figure, so we cannot compare hosting cost directly.
Which is cheaper to self-host, DB-GPT or LangBot?
DB-GPT: from €19.99/mo. LangBot: not estimated (no official RAM figure). Our estimate is the cheapest Hetzner Cloud plan that meets each project's official RAM and vCPU figure; it covers the server only.
How much hardware do DB-GPT and LangBot need?
DB-GPT: minimum 2 vCPU · 4 GB RAM · 10 GB disk. LangBot: not published.
What is the license difference between DB-GPT and LangBot?
DB-GPT: MIT (Permissive). Permissive. Internal and commercial use, modification and redistribution allowed; keep the copyright and license notice. LangBot: Apache-2.0 (Permissive). Permissive. Internal and commercial use allowed; keep license and notices. This is a summary, not legal advice.
Is DB-GPT or LangBot more actively maintained?
DB-GPT: Active, last commit Nov 2, 2026. LangBot: Active, last commit Nov 4, 2026. GitHub data refreshed Nov 4, 2026.
Which is easier to deploy, DB-GPT or LangBot?
DB-GPT installs via Docker Compose (web server + MySQL) (multi-container stack); LangBot via Docker Compose (multi-container stack). DB-GPT lists 4 known gotchas and LangBot lists 4; see each app page.
Related
- DB-GPT self-hosting guide · LangBot self-hosting guide
- All DB-GPT alternatives, ranked
- All LangBot alternatives, ranked
- Agent Zero vs DB-GPT
- Agent Zero vs LangBot
- AstrBot vs DB-GPT
- AstrBot vs LangBot
- AutoGPT Platform vs DB-GPT
- AutoGPT Platform vs LangBot
- CowAgent vs DB-GPT
- CowAgent vs LangBot
- Coze Studio vs DB-GPT
- Coze Studio vs LangBot
- DB-GPT vs Dify
- DB-GPT vs Flowise
- Add a third app in the interactive comparison
Sources
- DB-GPT GitHub repository: github.com/eosphoros-ai/DB-GPT
- DB-GPT documentation, DB-GPT deploy instructions: github.com/eosphoros-ai/DB-GPT/blob/main/docs/docs/getting-started/deploy/docker-compose.md
- DB-GPT license: github.com/eosphoros-ai/DB-GPT/blob/main/LICENSE
- DB-GPT hardware requirements: github.com/eosphoros-ai/DB-GPT/blob/main/docs/docs/getting-started/prerequisites.md
- LangBot GitHub repository: github.com/langbot-app/LangBot
- LangBot documentation, LangBot hardware requirements, LangBot deploy instructions: langbot.app/docs/en/deploy/langbot/docker
- LangBot license: github.com/langbot-app/LangBot/blob/master/LICENSE
- Hetzner Cloud pricing used for cost estimates (read 2026-11-01): www.hetzner.com/cloud/regular-performance
- GitHub REST API (stars, commits, releases): docs.github.com/en/rest
Every value is generated from the same verified data as the app pages. Spotted something wrong? Tell us.