Graph databases—like other NoSQL databases—typically use their own custom query methodology instead of SQL. One commonly used graph query language is Cypher , originally developed for the ...

Give me control of a database query language, and I care not who makes its engine. The noticeable spike in interest in graph in the last year can be largely attributed to heavyweights such as ...

Graph databases and relational databases have big differences when it comes to how connections work, ... (Related: NewSQL: Trying to solve what SQL and NoSQL can’t on their own) ...

Graph databases are proven architectures for storing data with complex relationships. ... The query is elegant and efficient but has a learning curve for those used to writing SQL queries.

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 ...

Unlike SQL databases, which can require complex queries to extract conclusions from data, graph databases execute queries more efficiently, and their advantage over SQL databases increases with ...

Why graph databases are becoming mainstream and their connection to AI, ML and big data use cases. ... said “graph databases will not replace the Oracle, SQL Server, MySQLs of the world; ...

Graph databases and models have been around for well over a decade, ... which make it possible, but not easy, to use familiar SQL query syntax to query the event streams.

TigerGraph today announced that the latest release of its parallel graph database can be fully controlled with Kubernetes. With version 3.2, the company also added the ability to scale the database up ...

Memgraph, a real-time graph database provider, today announced it has raised $9.34 million in a seed funding round led by Microsoft’s M12. The company also launched its community and enterprise ...