Many people have never heard of Wikidata, yet it’s a thriving knowledge graph that powers enterprise IT projects, AI assistants, civic tech, and even Wikipedia’s data backbone. As one of the world’s ...

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

As data complexity continues to grow and the demand for real-time insights increases, the move away from traditional relational databases and towards the adoption of graph databases will become vital.

In the age when data is everything to a business, managers and analysts alike are looking to emerging forms of databases to paint a clear picture of how data is delivering to their businesses. The ...

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 ...

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.

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.

With the global data science platform market size forecast to reach $322.9 billion by 2026 (up from $95.3 billion in 2021), staying informed and adapting to these advancements means leaders can ...

AWS, Google, Neo4j, Oracle. These were just some of the vendors represented in the W3C workshop on web standardization for graph data, and what transcribed is bound to boost adoption of the ...

SHACL allows a data graph, for instance, to specify the corresponding shapes graph used to describe the link between a given shape and targeted data. Franz claims its upgraded, flexible architecture ...