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The year of the graph: do you really need a graph database?

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Wednesday 14th

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17:05 | 17:45

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Theatre 18


Keywords defining the session:

- Graph databases

- Research

- Analysis

Takeaway points of the session:

- Keys to evaluating graph databases is understanding 1, their models, 2, your use cases


It is important to define what a graph database is and what it is not.
A number of solutions offer graph-related features or analytic capabilities.
We define graph databases as the ones having the ability to fully support operational applications utilizing a graph data model and API.

The major choice when it comes to graph databases is the one regarding graph data models.
LPG (Labeled Property Graph) and RDF (Resource Description Framework) are the two options.
Databases utilizing each tend to have specific characteristics, making them more suitable for specific use cases.

Not being based exclusively on a graph data model does not necessarily mean being ruled out.
Multi-model graph databases support LPG or RDF, plus models such as key-value and document.
This makes for a more diverse platform, albeit possibly at the expense of optimizing for graph.

Cloud-only solutions from AWS and Microsoft are different from the rest and from each other.
Their features in terms of scalability and availability appear similar.
Their technical features are different, and they are at different maturity points.