Using Your Data and Your Knowledge Differently – Graph Databases
Unlike other database management systems (DBMS), relationships take first priority in graph databases. In the graph world, the relationship between items of information is equally (or more) important than individual data points. This relationship is often superior at reflecting the “real world” that the data represents.
This connections-first approach to data means relationships and connections are permanent and highly customizable (and not just temporarily calculated) through every part of the data. The query language can navigate these relationships and the information located at each point rapidly.
Unlike other database systems, this approach means far more efficient queries which normally would require many joins, lookup tables, and transformations. Graph databases can combine many different types and sources of data together that would otherwise be difficult and expensive to achieve.
Organizations are under increasing pressure to provide actionable insights from operational data even as datasets grow larger and more unwieldy. The often require solutions that determine the connections between data points and derives appropriate cogent conclusions. Sometimes it requires the combination of organizational knowledge with the operational data to identify gaps or opportunities.
In these situations, Graph databases are part of the solution. They allow data professionals as well as end users at every level to exploit the potential of their data relationships rather than just individual data points, and the only limit to how those relationships might be harnessed is the imagination of the database user.
Graph database use is continuing to grow rapidly and also becoming accessible to more than just fortune 500 companies who have already begun to realize significant competitive advantages from this tool.
Graph databases are incredibly flexible. Their applications are limited only by the creativity of the data professionals modelling the structures. Here are some examples of graph database systems put to use in real-world applications:
5 noteworthy use-cases of Graph Technology & Analytics
Neo4j and Graph Database Use Cases
Industrial Equipment Warranty and Repair Management
Operational Process and Compliance
Operational Logistics & Tracking
Customer Relationship & ECommerce 360 Degree Analysis
How do graph databases work?
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