Google popularized the term "knowledge graph" in this 2012 blog post. Since then, there has been a massive momentum around ...

Graphs are ideal for handling these tasks. Graph algorithms are the driving force behind the next generation of AI and machine learning that will power even more industries and use cases.

Connecting And Leveraging Data. Knowledge graph technology is transforming the way that organizations manage and make sense of data: A Unified View: By integrating data from multiple sources ...

Nebula Graph provides an industry-best capability of storing and handling billions of vertices and trillions of edges, with just milliseconds of latency. Its shared-nothing deployment architecture, ...

The Graph, the open, universal data layer for web3, announced today a strategic integration with the TRON blockchain network. This integration leverages Substreams, a powerful streaming product ...

Graph analytics can be performed on any back end, as they only require reading graph-shaped data. Graph databases are databases with the ability to fully support both read and write, utilizing a ...

Graph data science is when you want to answer questions, not just with your data, but with the connections between your data points — that’s the 30-second explanation, according to Alicia Frame.

LinkedIn recently published how LIquid, its graph database, automates the indexing and real-time access of all connections to members, schools, skills, companies, positions, jobs, events, etc.

Graph analysis is a whole new area for GIS, according to Esri Founder and President Jack Dangermond, with the potential to promote various new kinds of data discovery, as graph technology informs ...

Until the nineteenth century, Friendly and Wainer tell us, most modern forms of data graphics—pie charts, line graphs, and bar charts—tended to have a one-dimensional view of their data ...