Vanna.ai

Vanna is a Python framework (and hosted cloud product) that turns natural-language questions into executable SQL against your own database. It connects to SQLite, Postgres, MySQL, Snowflake, BigQuery and other common engines, runs a RAG layer over your DDL, documentation, and example queries, then asks the LLM of your choice to produce a query, execute it, and return results plus a chart. The 2.0 release adds multi-turn conversations and an admin layer with access control, audit logs, and observability.

The differentiator is honesty about how text-to-SQL actually works: instead of pretending one zero-shot prompt is enough, Vanna leans on a trainable vector store of your schema and prior good queries, and it's model-agnostic across Anthropic, OpenAI, Gemini, and local Ollama. The core framework is MIT-licensed and self-hostable for free; the cloud tier is for teams that want a managed vector store, governance, and a hosted UI rather than wiring Streamlit/Flask themselves. It's aimed at data teams who want analyst-style self-serve without handing the warehouse to a black-box SaaS.

Because it's a library first, integrations are flexible: bring your own LLM, your own vector DB (Chroma, pgvector, Pinecone, etc.), and your own front-end. The trade-off is that quality scales with how much training data (DDL + curated Q/SQL pairs) you feed it, and it inherits whatever the underlying LLM gets wrong about joins on messy schemas.