Graph databases are the fastest-growing category in all of data management. Graph databases have evolved into a mainstream technology that has been successfully implemented by organizations in ...

New techniques make graph databases a powerful tool for grounding large language models in private data. Once you get past the chatbot hype, it’s clear that generative AI is a useful tool ...

The Global Graph Database Market size is expected to reach $8.1 billion by 2028, rising at a market growth of 22.2% CAGR during the forecast period.A graph database is a single-pu ...

Graph databases are slower and more resource-consuming for insert performance than relational databases. However, in most applications, records are read many more times than they are inserted or ...

The emergence of generative AI is fueling new demand for graph databases, which previously were used in somewhat niche applications like fraud detection. That’s good news for Neo4j, which holds the ...

The appetite for connected data is fueling a shift from traditional relational databases to interconnected graph-based models. This evolution promises deeper insights and can facilitate a more ...

Graph databases are used for social graphs, fraud detection, and recommendation engines, and there are simplified versions of these applications that you can build based on pre-existing data sets ...

REDWOOD CITY, Calif., March 04, 2025 (GLOBE NEWSWIRE) — TigerGraph, the enterprise AI infrastructure and graph database leader, today announced its next generation graph and vector hybrid search ...

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 ...