Semantic Graph

Semantic Graph is a structured, network-based data model where nodes represent concepts or physical assets, and directed edges represent the explicit, logical relationships between them. It provides a formal framework for representing domain knowledge, ensuring that relationships carry explicit, machine-readable meanings.

How it Works

A semantic graph processes data using defined ontologies and vocabularies. It models assertions as subject-predicate-object triplets, defining how distinct data elements interconnect.

• Ontological Constraints: Rules that define valid node classifications and edge relationships, preventing illogical links.
• Graph Traversal: Algorithms query the network by following edge paths, resolving complex joins across disparate datasets dynamically.

Lakehouse & Agentic Relevance

In a data lakehouse, a semantic graph maps raw table schemas and virtual views to logical business concepts. For autonomous agents, the graph provides an actionable map of the data ecosystem. The agent queries the semantic graph to determine which tables contain the fields necessary to compute a business metric, avoiding the need to scan entire databases. Dremio facilitates the creation of semantic graphs by providing unified virtual datasets that abstract underlying data sources, allowing catalogs like Apache Polaris to govern and index these relationships.