Explore
Try CrateDB Live
- 1. Run CrateDB
- 2. Choose Scenario
- 3. Get Ready
- 4. Import Data
- 5. Explore Queries
- 6. More Queries
- 7. Connect
- 8. Next Steps
CrateDB can be used as a backend for AI and LLM-based applications, particularly for:
- Retrieval-Augmented Generation (RAG)
- Time-series analytics for AI workflows
- Real-time data enrichment
- LangChain
- LlamaIndex
- Custom Python-based AI pipelines
In most cases, you simply provide:
- Host:
<your-host> - Port:
5432 - Username:
crate - Database:
demo
Your AI application can then query CrateDB in real time using SQL.