By multi-model, Franz said its semantic graph database supports ingestion of different JSON documents as well as Resource Description Framework (RDF), or triplestore, data—another World Wide Web ...

A sui generis, multi-model open source database, designed from the ground up to be distributed. ArangoDB keeps up with the times and uses graph, and machine learning, as the entry points for its ...

Key-value, document-oriented, column family, graph, relational… Today we seem to have as many kinds of databases as there are kinds of data. While this may make choosing a database harder, it ...

Data Squared (Data²), a small business dedicated to helping public and private sector organizations unlock the full potential of their data, is partnering with Neo4j, a leading graph database and ...

By combining ontology and large language model-driven techniques, engineers can build a knowledge graph that is easily queried and updatable.

Emerging graph database benchmarks are already helping to overcome performance, scalability and reliability issues.

Graph databases store data as a network of interconnected facts. This type of data model is useful for researchers to easily and quickly map and analyse complex connections.

Combining both graph databases and knowledge graphs “enables you to derive maximum benefit with GenAI and large language model technologies,” said Biswas. “A high-performance graph database with a ...

Available starting today, Neo4j Aura Graph Analytics is said to work with any kind of data source, including Oracle, Microsoft SQL, Databricks, Google BigQuery, Snowflake and Microsoft OneLake.