Seven enterprises using graph databases: Popular graph database use cases, from recommendation engines to fraud detection and search

The 7 most common graph database use cases in the enterprise, and the businesses running them

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Back in 2014 Forrester predicted that 25 percent of enterprises would be using graph databases by 2017, with typical use cases hinging on spotting patterns in big data platforms to eliminate fraud, make recommendations and improve network operations.

It’s a favourite stat of the popular graph database vendor Neo4j, namely because it can benchmark against it for its own enterprise-scale graph database. Today the vendor claims to have almost half of the Forbes Global 2000 companies running some form of its graph database, either in production or as a pilot.

Speaking at Neo4j's annual GraphConnect conference in London this week, CEO Emil Eifrem ran through the seven most common use cases they are seeing in the enterprise.

Read next: What is a graph database? Graph database vendors, graph database use cases and graph database customers explained

Naturally, Eifrem was keen to state that graph databases are a fundamentally “horizontal proposition” and that the below use cases are just the work of early adopters.