DB-GPT vs Mem0
Short answer
DB-GPT: AI data assistant that connects to your databases, writes SQL and code, and turns analysis into reports. Mem0: Long-term memory layer for AI assistants and agents, with a self-hosted REST server and dashboard. Both are in our AI app & agent builders category.
Choose Mem0 if you want: larger community (68.3k vs 20.2k GitHub stars).
Mem0 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 Mem0 side by side
| DB-GPT | Mem0 | |
|---|---|---|
| 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. | Long-term memory layer for AI assistants and agents, with a self-hosted REST server and 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. | Free for internal and commercial use, modification and redistribution. Keep the license and NOTICE text and state significant changes when you redistribute. |
| Status | Active | Active |
| GitHub stars | 20.2k | 68.3k |
| Last commit | Nov 2, 2026 | Oct 30, 2026 |
| Latest release | v0.8.2 | ts-v3.3.1 |
| 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 (build from source) |
| Known gotchas | 4 listed | 4 listed |
| Telemetry | Not documented | On by default |
| Calls home by default | Not documented | Not documented |
| SSO (OIDC / SAML / LDAP) | Not documented | Not documented |
| Audit log | Not documented | Yes, free |
| RBAC | Not documented | Not documented |
| Details | Full DB-GPT guide → | Full Mem0 guide → |
Key differences
- License: DB-GPT: MIT (Permissive). Mem0: Apache-2.0 (Permissive).
- Official hardware: DB-GPT: minimum 2 vCPU · 4 GB RAM · 10 GB disk. Mem0: not published.
- GPU: DB-GPT: optional / see notes. Mem0: not required or not stated.
- Est. server cost: DB-GPT: from €19.99/mo. Mem0: not estimated (no official RAM figure).
- Deploy: DB-GPT: Docker Compose (web server + MySQL) · multi-container stack. Mem0: Docker Compose (build from source) · multi-container stack.
- GitHub stars: DB-GPT: 20.2k. Mem0: 68.3k.
- Last commit: DB-GPT: Nov 2, 2026. Mem0: Oct 30, 2026.
- Latest release: DB-GPT: v0.8.2 (Aug 26, 2026). Mem0: ts-v3.3.1 (Sep 25, 2026).
Same for both: Category: AI app & agent builders; Status: Active.
DB-GPT vs Mem0: FAQ
DB-GPT or Mem0: which should a small business choose?
Choose Mem0 if you want: larger community (68.3k vs 20.2k GitHub stars). Mem0 publishes no official RAM figure, so we cannot compare hosting cost directly.
Which is cheaper to self-host, DB-GPT or Mem0?
DB-GPT: from €19.99/mo. Mem0: 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 Mem0 need?
DB-GPT: minimum 2 vCPU · 4 GB RAM · 10 GB disk. Mem0: not published.
What is the license difference between DB-GPT and Mem0?
DB-GPT: MIT (Permissive). Permissive. Internal and commercial use, modification and redistribution allowed; keep the copyright and license notice. Mem0: Apache-2.0 (Permissive). Free for internal and commercial use, modification and redistribution. Keep the license and NOTICE text and state significant changes when you redistribute. This is a summary, not legal advice.
Is DB-GPT or Mem0 more actively maintained?
DB-GPT: Active, last commit Nov 2, 2026. Mem0: Active, last commit Oct 30, 2026. GitHub data refreshed Nov 3, 2026.
Which is easier to deploy, DB-GPT or Mem0?
DB-GPT installs via Docker Compose (web server + MySQL) (multi-container stack); Mem0 via Docker Compose (build from source) (multi-container stack). DB-GPT lists 4 known gotchas and Mem0 lists 4; see each app page.
Related
- DB-GPT self-hosting guide · Mem0 self-hosting guide
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- 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
- Mem0 GitHub repository: github.com/mem0ai/mem0
- Mem0 documentation: docs.mem0.ai/open-source/overview
- Mem0 license: github.com/mem0ai/mem0/blob/main/LICENSE
- Mem0 hardware requirements, Mem0 deploy instructions: github.com/mem0ai/mem0/blob/main/server/README.md
- 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.