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Try CrateDB Live

  • 1. Choose Scenario
  • 2. Get Ready
  • 3. Run CrateDB
  • 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
You can connect to CrateDB from AI frameworks using standard PostgreSQL drivers or HTTP APIs, making it straightforward to integrate with tools such as:
  • 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.