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The Semantic Graph Platform

Timbr is an SQL-native knowledge graph that turns your databases into reasoning machines.

Timbr delivers the powers of knowledge graphs to the SQL data ecosystem with an easy-to-use no-code UI or with standard SQL statements.

The platform installs on top of existing databases to enable the creation of virtual semantic models mapped to the underlying data and provides seamless connectivity to the popular BI and data science tools in use by organizations.


Timbr is accessible using JDBC, ODBC, REST API:

Timbr integration

Platform components

Model, Visualize, Manage, and Query your data as a connected semantic graph

Ontology ExplorerGraph ExplorerKnowledge GraphsSQL Editor
Data MapperKnowledge LineageDatasourcesQuery Search
Ontology ViewsPerformance DashboardMaster Data ManagementSaved Queries
ChartsScheduled Jobs
DashboardsAccess Manager
CSS TemplatesRecent Activity
Saved Explorations


  • Ontology Modeling: represent an abstract, simplified view of the world with conceptual schemas.
  • Business Rules: embed business logic and rules into the data model.
  • Virtualization: no ETL required. Distributed JOINs/UNIONs and Push-down optimizations.
  • Graph Traversals: graph traversals in standard SQL without the need to explicitly write joins.
  • Inheritance: is-a relationships provides higher level of abstraction than SQL views.
  • Inference: infer new knowledge and relationships based on a set of rules on the data.
  • Data Exploration: an intuitive interface for exploring and visualizing data.
  • NoSQL Capabilities: allowing a relatively flexible schema declaration and evolution.
  • Integration: supports most SQL Engines, NoSQL, and data formats.
  • Materialization: 3-tier cache engine - Datalake, SSD, OLAP In-memory.
  • Master Data Management: Import and edit master-data live in the Timbr platform.
  • Apache Spark and Databricks Native: available in DataFrames on Java, Scala, R and Python.