Graph database query languages are growing, along with graph databases. They let developers ask complex questions and find relationships.

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. If there is a ...

GSQL combines SQL-like query syntax with Cypher-like graph navigation, plus procedural programming and user-defined functions. TigerGraph can convert Cypher to GSQL for people moving from a Neo4j ...

The similarities between relational databases and semantic graph databases allow for a natural evolution of user skills, which is substantially more cost efficient than having to finance a slew of ...

The benefits of graph databases go beyond mere query speed. Complex relational models no longer need to be hammered out in the usual, arduous manner because relationships can be modeled easily and ...

Graph analytics will grow in the next few years due to the need to ask complex questions across complex data, which is not always practical or even possible at scale using SQL queries".

One of the human costs of replacing a SQL database with Neo4j is education: learning the Cypher query language, the two libraries, and graph database design. (A similar statement could be made ...

Graph querying of data housed in massive data lakes and data warehouses has been part of the big data and analytics scene for many years, but it hasn’t always been a particularly easy process.

The relational database is primarily oriented toward the modeling of objects (entities) and relationships. Generally, the relational model works best when there are a relatively small and static ...

A peek at DB-Engines graph database comparison (graphed in a slightly non-intuitive logarithm scale) shows steady growth for Neo4j. Titan and OrientDB, a multi-modal database, show some growth. But ...