Dify vs Khoj
| Tagline | Open-source LLM app development platform with visual workflow, RAG, and agent builder | Personal AI second brain: search your docs, schedule automations, do deep research |
| Category | AI & LLM Tools | AI & LLM Tools |
| Replaces | ChatGPT, OpenAI API | ChatGPT, OpenAI API |
| GitHub stars | 150k | 36k |
| Language | Python | Python |
| License | Apache-2.0 | AGPL-3.0 |
| Self-host difficulty | 3/5 Moderate | 3/5 Moderate |
| Deploy options | Docker Compose Kubernetes | Docker Manual |
| Managed hosting | ||
| Last updated | 6 days ago | 1 month ago |
| View repo | View repo |
Where each falls short
The honest trade-offs — what you give up with each, versus the proprietary tools they replace.
Dify
- Self-hosted community edition lacks SSO and audit logs (cloud-only)
- Requires multiple services (Postgres, Redis, Weaviate/Qdrant) increasing ops burden
- Plugin marketplace is smaller than commercial AI platforms
Khoj
- Real-time web search index is shallower than Perplexity or Bing-backed tools
- Team/multi-user collaboration features are limited in self-hosted mode
- Scheduled automations require careful setup and may drift without monitoring
- Mobile apps are basic compared to consumer AI assistants
Bottom line
Both are a similar lift to self-host; choose Dify for the larger community and ecosystem. Dify has seen more recent development. Open each guide below for deploy steps and the full feature gap.