smart capabilities
Graph
Analytics
(on Relational Data)
Timbr’s Graph Analytics applies powerful graph algorithms to relational data leveraging the ontologies’ relationships – no graph database needed.
Users uncover insights directly on governed data from Databricks, Snowflake, BigQuery, and more, within a SQL-native environment.
Key Capabilities
Run Graph Algorithms on Relational Data
Apply algorithms like PageRank, Shortest Path, Community Detection, and Centrality directly to your tabular data modeled as a semantic graph.
No Graph Database Required
Leverage the relational infrastructure you already have. Timbr virtualizes the graph model and runs the computations in optimized SQL.
Integrate with BI Tools and Workflows
Output algorithm results as virtual tables or views, accessible from dashboards, notebooks, or analytics pipelines.
Governed, Explainable, Reproducible
All graph logic is defined through transparent, SQL-based ontologies, ensuring consistency, explainability, and compliance.
Built for Data Scientists & ENGINEERS
Run graph analytics using SQL or REST interfaces, no need to learn Cypher, Gremlin, or SPARQL.
