Neo4j Inc. today released what it calls the most significant evolution of its graph database engine since the company was founded in 2007.The 4.0 release features unlimited scalability, intelligen ...

In its new release, Neo4j addresses key concerns for enterprise adoption. Scalability, security, management and architectural changes are here. And so is a strange feeling of deja-vu, too.

Graph database vendors are broadening their applications by adding enterprise-focused features to help customers who are dealing with the burdens of huge troves of business-critical data. In a move ...

Graph databases represent one of the fastest-growing areas in the database market. MarketsandMarkets’ report on graph databases predicts that graph databases will grow from $1.9 billion in 2021 to ...

The Bulgarian graph database startup Graphwise today announced a major upgrade to its flagship GraphDB tool, adding new features aimed at boosting enterprise knowledge management and creating a more ...

Neo4j Graph Database 4.0 has been released with a new reactive architecture to provide a “very responsive, elastic and robust” database, the company explained.

“Today, graph databases in Neo4j are being widely deployed across the enterprise, and now all of a sudden there’s multiple teams across the entire enterprise that wants to access the data.

The figure below illustrates this modern heterogeneous enterprise data architecture. Clouds in the Forecast Although the modern non-relational distributed architectures which inspired databases such ...

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 ...

TigerGraph, a well-funded enterprise startup that provides a graph database and analytics platform, today announced that it has raised a $105 million Series C funding round.The round was led by ...

In recent years, knowledge graphs have become an important tool for organizing and accessing large volumes of enterprise data in diverse industries — from healthcare to industrial, to banking ...

Graph databases are playing a growing role in improving fraud detection, recommendation engines, lead prioritization, digital twins and old-fashioned analytics. But they suffer performance ...