auto-ontology vs vanna
Enterprise data context and natural-language SQL compared
auto-ontology and vanna both help agents or users ask questions about SQL data in natural language. auto-ontology builds a semantic context layer from enterprise metadata, while vanna provides components and tools for embedding conversational SQL experiences in applications.
auto-ontology: Ground Agent Queries in Enterprise Data with NVIDIA NIM
NVIDIA Auto Ontology builds a semantic context layer from enterprise metadata, helping agents generate more reliable, explainable data queries. It uses NVIDIA NIM for inference and exposes context through MCP, a CLI, and an API.
vanna: Turn Natural-Language Questions into SQL Insights
Vanna helps teams build chat interfaces that translate natural-language questions into SQL and return streamed tables, charts, and summaries. It is aimed at applications that need database-backed answers with user-aware permissions and an embedded web UI.
| auto-ontology | vanna | |
|---|---|---|
| Language | Python | Python |
| License | Apache-2.0 | MIT |
| Stars | 738 | 23.8k |
| Forks | 90 | 2.5k |
| Last analyzed | Nov 2, 2026 | Oct 3, 2026 |
Key differences
- auto-ontology builds an ontology from metadata and connects semantic models, definitions, and lineage; vanna focuses on an LLM-backed agent that translates questions into SQL.
- auto-ontology provides a web application and exposes context through MCP, a CLI, and an API; vanna offers an embeddable web chat component and integrations with FastAPI and Flask.
- auto-ontology supports Docker Compose and Kubernetes Helm deployments; vanna is a framework for applications whose teams configure their own database access and security policies.
- auto-ontology is licensed under Apache-2.0 and is not archived; vanna is licensed under MIT and is marked archived.
- auto-ontology is suited to teams reconciling enterprise metric definitions and grounding answers in certified definitions and lineage; vanna is suited to product teams embedding streamed tables, charts, and summaries with user-aware permissions.
Choose auto-ontology if you…
- need a semantic context layer built from enterprise metadata and existing models.
- want to check generated queries against certified definitions and lineage, with provenance.
- need MCP access or a self-hosted application deployable with Docker Compose or Kubernetes.
Choose vanna if you…
- want to embed a natural-language SQL chat interface in an existing application.
- need streamed tables, charts, and summaries or user-aware permission handling.
- want integrations with web frameworks, LLM providers, and database systems, and can account for the repository's archived status.
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This comparison is generated with AI from the OSRepos analyses of both projects. Always check each project's repository and documentation before choosing.