The top 5 use cases of graph databases
Big data” grows bigger every year, but today’s enterprise leaders don’t only need to manage larger volumes of data, but they critically need to generate insight from their existing data.
Big data” grows bigger every year, but today’s enterprise leaders don’t only need to manage larger volumes of data, but they critically need to generate insight from their existing data. So how should CIOs and CTOs generate those insights?
To paraphrase Seth Godin, businesses need to stop merely collecting data points, and start connecting them. In other words, the relationships between data points matter almost more than the individual points themselves.
In order to leverage those data relationships, your organisation needs a database technology that stores relationship information as a first-class entity. That technology is a graph database.
Ironically, legacy relational database management systems (RDBMS) are poor at handling relationships between data points. Their tabular data models and rigid schemas make it di cult to add new or different kinds of connections.
Graphs are the future. Not only do graph databases effectively store the relationships between data points, but they’re also flexible in adding new kinds of relationships or adapting a data model to new business requirements.
So how might your enterprise leverage graph databases to generate competitive insights and significant business value from your connected data?
Find out about the top five use cases of graph database technologies.