I co-created Graph Neural Networks while at Stanford. I recognized early on that this technology was incredibly powerful. Every data point, every observation, every piece of knowledge doesn’t exist in ...

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 ...

For a long time, companies have been using relational databases (DB) to manage data. However, with the increasing use of ...

A research team led by Bing Qin introduces a novel method for Knowledge Graph Completion using higher-order neighbor subgraphs to address sparsity issues, demonstrating its effectiveness in a ...

Nov. 11, 2021 — TigerGraph, provider of the leading graph analytics platform, has announced its enhanced Graph Data Science Library (previously named the GSQL Graph Algorithm Library.) This latest ...

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

New architecture fuses real-time transactions and analytics in one platform, with breakthrough performance and full fidelity at unprecedented scale Neo4j, the leading graph database and analytics ...