Some graph databases require you to define a schema for your graph—i.e. defining labels or names for your vertices, edges, and properties prior to populating any data—while other databases ...

IBM Graph works with a schema to create indexes that are used for querying data. The schema defines the data types for the properties that will be employed and allows for the creation of indexes ...

Graph technology is well on its way from a fringe domain to going mainstream. We take a look at the state of the union in graph, featuring Neo4j's latest release and insights as well as data and ...

Also: AWS Neptune going GA: The good, the bad, and the ugly for graph database users and vendors There can be many applications for these knowledge graphs -- from cataloguing items, to data ...

Google is now leveraging linked data within the enterprise, which is very clear within the “Knowledge Graph,” and in some fashion, they are doing so with the consumed information from rich ...

Graph database pioneer Neo4j announced the latest update of its namesake product this week, and the company isn't holding back on the superlatives. Neo4j 4.0 is "the most significant product release ...

This week, we are taking a look at TigerGraph, one of the upstart graph database makers that is taking on the incumbent commercial graph database, Neo4j, as well as a slew of open source projects like ...

Graph databases are among most promising new analytic solutions in visualizing data relationships that matter. What's more, they are excellent analytic complements to your DAM.

Graph-relational database developer EdgeDB Inc. is gearing up for prime time after closing on a $15 million early-stage round of funding ahead of its official launch early next year.

For example, TigerGraph recently used these benchmarks to scale its database to support 30 terabytes (TB) of graph data, up from 1 TB in 2019 and 5 TB in 2020.