The author is Chief Scientist at graph database platform leader Neo4j and Visiting Professor at Newcastle University. Read Jim Webber's full executive profile here.
It wasn’t very long ago that if I wanted to start a new enterprise software company, a new fintech payments service or a new cloud payroll service, I’d have selected a relational database management system such as Oracle, IBM Db2 or Microsoft SQL Server as the data foundation for my serious system.
The world is more connected, and our data is more intricate than it was in the dominant era of the relational database. And CIOs want greater flexibility and firepower.Steve Scalise Abruptly Withdraws From House Speaker Race A Day After GOP Nomination Today, jobs are far more complex. Someone might be in a job where they have stock options while their colleague has a quarterly bonus structure that’s dependent on sales figures. A fellow co-worker has an additional stock award for a special achievement, while another has private medical insurance, and others enjoy electric bike subsidies. Some just have salaries and no extra benefits.
For many contemporary business systems, this set of fundamental design choices is limiting. It makes more sense to work with data models that better reflect your business domain than try to squeeze it into a classical data model, with its strict rules about rows, tables and schema. I’m not saying an individual’s profile couldn’t be captured in relational. But talking about this individual in all their complexity is easier in a system that is open to arbitrary interconnections. Dealing with connections as first-class citizens gives you a lot more ambition. For instance, you can launch a new enterprise software company, a fintech payments service or a cloud payroll service. If your ambition is unfettered and your competitors remain constrained—you win.
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