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 ...

These systems, which link data through foreign keys and joins, ... For example, graph databases excel in environments where relationships drive functionality, ...

One of the best-known graph databases is Neo4j, which recently announced support for the enterprise version of its cloud-hosted service, Aura, on Azure.Available in the Azure Marketplace, it’s a ...

We had a chance to speak with TigerGraph's incoming head of product R&D, and it spurred some thoughts on where we thought graph databases should go.

agamemnon is a Python-based graph database built on pycassa, the Python client library for Apache Cassandra. In short, it enables you to use Cassandra as a graph database. The API is inspired by ...

Imagine a graph database that's not aimed at the growing graph database market, selling to Fortune 500 without sales, and claiming to be the fastest without benchmarks. Dgraph is unique in some ...

"Graph databases offer a data model that allows for the expression of connections in a very robust fashion," Eifrem said. "Relationships in the graph data model are first class citizens. That is not ...

TigerGraph Inc. has launched its managed graph database on Google Cloud, enabling customers of the search giant’s infrastructure-as-a-service platform to use the software in their analytics projects ...

In a graph database, data is represented by nodes, edges and properties. Nodes are the familiar objects that we might model in a RDBMS or key-value store - customers, products, parts, web pages, etc.

Graph databases are different from relational in several key ways. While you can build some relationships between tables in a relational database, there are limits and the more data you have the ...