neocarta vs ontobricks
Neo4j Labs' semantic layer for data agents: ingest warehouse schema, business glossary, metrics and query history into one graph, then serve it over MCP so agents route queries and write grounded SQL. — versus — Turns Databricks Unity Catalog tables into a materialized knowledge graph: OWL ontology design, R2RML mapping, OWL 2 RL/SWRL/SHACL reasoning, auto-generated GraphQL — exposed to agents over MCP.
The same catalog → knowledge graph → MCP pipeline aimed at Databricks Unity Catalog, with OWL ontology design, R2RML mapping and OWL 2 RL/SHACL reasoning. Choose by stack and by taste: formal ontology and reasoning versus Neo4j property graph and hybrid search.
| neocarta | ontobricks | |
|---|---|---|
| Stars | 98 | 297 |
| Forks | 26 | 52 |
| Language | Python | Python |
| License | Apache-2.0 | NOASSERTION |
| Last activity | 4 days ago | yesterday |
| Topics | knowledge-graphs, data | knowledge-graphs |
| Curated connections | 5 | 8 |
neocarta — the curator's take
The honest fix for Text2SQL: the model is not bad at SQL, it is blind to your data landscape. Neocarta pulls schema metadata, foreign keys, sample values, glossary terms, governed metric definitions and real query history into a Neo4j graph — only metadata crosses over, data stays in the source — then serves it to agents over MCP with full-text, vector and hybrid search that returns columns, types, example values and the FK references needed to build a join. Embeddings are optional; catalog search works from schema alone. It ships a runnable LangGraph + BigQuery agent so you can see the routing loop end to end. Read the label though: Neo4j Labs, explicitly experimental, not a supported product, 98 stars, and it assumes you are willing to stand up and maintain a Neo4j instance next to your warehouse.
ontobricks — the curator's take
The only tool here that gives agents a REASONED graph — OWL 2 RL/SWRL inference over your warehouse, not just edges — and the four-click LLM-assisted pipeline from table metadata to queryable ontology is genuinely novel. When NOT: anywhere outside Databricks — it hard-requires Unity Catalog, Lakebase Postgres and Databricks Apps. Labs project: no SLA, ★254 young. For lakehouse graph context without the platform lock-in, look at omnigraph.