Graph technology has become a requirement for the modern enterprise. Companies in virtually every industry, from healthcare to energy to financial services, are applying the power of graph analytics ...

Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. Agent workflows make transport a first-order ...

How would you feel if you saw demand for your favorite topic — which also happens to be your line of business — grow 1,000% in just two years’ time? Vindicated, overjoyed, and a bit overstretched in ...

As the sources, types, and amounts of data continue to expand, so will the need for different kinds of analytics to make something of that data. Unfortunately, there is not a one-size-fits-all ...

Graph database vendor Neo4j Inc. is teaming up with Snowflake Inc. to make a library of Neo4j’s graph analytics functions available in the Snowflake cloud. The deal announced today allows users to ...

SAN FRANCISCO--(BUSINESS WIRE)--PuppyGraph, the first and only graph query engine, announced today its $5 million seed funding round led by defy.vc. The zero-ETL unlocks real-time graph analytics for ...

We have entered an era where e-Commerce rules retail. Consider how reports project online sales to hit more than $4 trillion by 2020, representing 14.6% of total retail spending worldwide (source: ...

BOSTON--(BUSINESS WIRE)--Cambridge Semantics, the leading provider of a universal semantic layer for big data management and connected data analytics solutions, today announced a preview of AnzoGraph, ...

Graph databases offer a more efficient way to model relationships and networks than relational (SQL) databases or other kinds of NoSQL databases (document, wide column, and so on). Lately many ...

As data ecosystems become more complex, organizations are looking for advanced tools and technologies to manage and derive value from diverse and interconnected data sources. Knowledge graphs provide ...

Probabilistic graphs and uncertain data analysis represent a rapidly evolving research domain that seeks to reconcile the inherent imprecision of real-world data with robust computational models. By ...