The number one graph database, Neo4j, is kicking off its Graph Connect event today and announcing a new version, 3.3. This version brings extended support for querying in Spark, ETL, analytics ...

(Image: DB engines) The gist of what's going on is that we have a war for graph database domination, and query language is a key battle to be won. SQL did not arrive at universal adoption overnight.

Consequently, most commercial graph and vector databases include support for the most common SQL commands, encapsulated in the ISO/ANSI SQL-92 standard. Where relational databases represent data as ...

IBM releases Graph, a service that can outperform SQL databases by Dan Richman on July 27, 2016 at 3:25 pm Share 1 Tweet Share Reddit Email ...

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.

Many graph insiders expect Cypher to become the standard language that allows graph databases to be searched, regardless of the product involved, which will power strong growth for the entire market.

As graph database adoption accelerates, new data infrastructures will emerge to eliminate many of the scale struggles of graph database models. Written by eWEEK content and product recommendations ...

Therein lies the first challenge for organizations moving toward graph databases: SQL is a pervasive skill set, and Cypher and other graph query languages are a new skill to learn.

TigerGraph, maker of the TigerGraph native parallel graph database designed for deep link analytics, has introduced TigerGraph Cloud, a graph database-as-a-service platform. The service, priced on ...

Ever since it emerged four years ago with a graph database that scales out natively on clusters of up to 1,000 nodes, TigerGraph has been pushing the boundaries of what a property graph database can ...