Visual ontology design
Drag-and-drop entities, relationships, and class hierarchies on the OntoViz canvas. Or import FIBO, CDISC, IOF and other OWL/RDFS standards.
Databricks Labs · Open Source
Turn your Databricks tables
Turn your Databricks tables
into a living knowledge graph
OntoBricks designs ontologies, maps them to Unity Catalog tables, materializes triples into a triple store, reasons over the graph, and serves it to your apps and AI agents — the full pipeline in four clicks.
OWL / RDFS
R2RML
Lakebase · Lakehouse · Neo4j
OWL 2 RL · SWRL · SHACL
GraphQL
MCP
01
Design
Ontologies in OWL — visually or LLM-generated
02
Map
Entities to Unity Catalog tables via R2RML
03
Reason
OWL 2 RL, SWRL rules & SHACL checks
04
Serve
GraphQL API & MCP for AI agents
What it does
Semantic web power, Databricks-native
OntoBricks brings ontologies, reasoning, and graph exploration to the Lakehouse — without leaving Unity Catalog or writing a single triple by hand.
AI-assisted mapping
An LLM wizard writes the SQL that binds ontology entities to your tables, column by column — then auto-maps everything else in a single batch.
Materialized triple store
Turn mappings into triples in the backend you choose — Lakebase (Postgres), Lakehouse (Delta) or Neo4j — incremental by default, no manual SQL.
Formal reasoning
Run OWL 2 RL deductive closure, SWRL business rules, transitive/symmetric expansion, and W3C SHACL data-quality validation over the graph.
Typed GraphQL API
A GraphQL schema is generated from your ontology at runtime — traverse nested relationships in a GraphiQL playground, per project.
MCP for AI agents
Expose the knowledge graph to LLM agents through the Model Context Protocol — connect from Cursor, Claude Desktop, or the Databricks Playground.
The pipeline
From metadata to knowledge graph in four clicks
LLM-powered automation handles the heavy lifting — you stay in control at every step.
1
Import metadata
Fetch table and column metadata straight from Unity Catalog. OntoBricks reads your schema so it understands what it's modeling.
2
Generate the ontology
An LLM designs entities, relationships, and attributes from your metadata — a fully editable starting point on the visual canvas.
3
Auto-map to tables
Generate R2RML mappings for every entity and relationship, with multi-pass column matching and partial-mapping detection.
4
Synchronize & explore
Materialize triples into the store, then query with GraphQL or explore the interactive, WebGL-powered knowledge graph.
Inside the app
See it in action
Watch & learn
Videos from the datacorner channel
Walkthroughs, release highlights, and deep dives. View the full playlist ↗
Get started
Up and running in minutes
bash
# Clone the repository
git clone https://github.com/databrickslabs/ontobricks
cd ontobricks
# Install dependencies with uv
uv sync
# Configure your Databricks credentials
cp .env.example .env
# edit .env → host, token, SQL warehouse ID
# Start the app → http://localhost:8000
./start.sh
bash
# Authenticate against your workspace
databricks auth login --host https://<workspace>
# Deploy as a native Databricks App
make deploy
# Then bind the sql-warehouse & volume resources
# in Compute → Apps → ontobricks → ResourcesPrerequisites
- Python 3.10+
- A Databricks workspace with Apps enabled
- A SQL Warehouse
- A Unity Catalog Volume for the registry
- Databricks Lakebase (v0.4.0+)
Under the hood
Built on open standards & the Lakehouse
OntoBricks stitches together semantic-web standards, graph databases, and formal reasoning on top of the Databricks Platform. Ontologies compile to R2RML, mappings become Spark SQL, and triples land in Lakebase, Delta or Neo4j — all governed by Unity Catalog.
- Multi-engine backend — Lakebase (Postgres), Lakehouse (Delta) or Neo4j, per domain.
- Version lifecycle — domains move through DRAFT → IN-REVIEW → PUBLISHED with audit trails.
- Managed-synced mode — delegate bulk movement to Lakeflow snapshot pipelines.
Community
Built by contributors
OntoBricks is open source and welcomes contributions. See everyone on GitHub ↗
Ready to build your knowledge graph?
Open source, Databricks-native, and yours to explore.