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 opinions from Cloudera, DataStax, and IBM.

Polyglot persistence is becoming the norm in big data. Gone are the days when relational databases were the one store to rule them all; now the notion of using stores with data models that best align with the problem at hand is becoming increasingly popular and understood.

Graph is a data model that has long lingered on the fringe of mainstream adoption. One of those things that few had heard of, fewer really knew and fewer yet actually used. But that is rapidly changing, as the benefits of graph are becoming pronounced and graph use cases, awareness and adoption are on the rise.

A few days ago, IBM released “The State of Graph Databases Worldwide,” a report on the adoption and use case characteristics of graph databases. The report features a survey with responses from 1,365 entrepreneurs and developers in diverse industries across 74 countries about the potential they see for graph databases as well as their current and planned use for this technology.

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