DataStax Enterprise
DataStax Enterprise Graph
Super-powering your data relationships.
WHY Graph?
Part of the always-on DataStax Enterprise data platform, DSE Graph is the first graph database powerful enough to scale to massive datasets while offering advanced integrated tools capable of deep analytical queries. Powered by the best distribution of Apache Cassandra™, DSE Graph can handle billions of items and their relationships spanning hundreds of machines across multiple datacenters with no single point of failure - the only thing it’s missing is a cape.
 
DSE Graph is the first graph database fast enough to power your real-time apps with effortless scale. The graph data model makes it easy to connect and use the relationships between your data. It’s like a standard relational database JOIN with superpowers, and with these powers you’ll be able to surface better insights to your users.
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DSE Graph
Complex relationships made simple
DataStax Enterprise Graph is made up of vertexes (objects) and edges (the relationship between objects).
Vertexes are designed to have many edges, which makes it easy for you because there’s no need for complex mapping tables. Got that? Quiz coming later.
Flexible data model
DataStax Enterprise Graph delivers agility and ease of use. The flexible and user-friendly data model lets you
add key relationships on the fly, freeing you to iterate and innovate with the powerful open-source query
language, Gremlin. DSE Graph enables up to 110 times less code than a similar relational database-backed
solution (so if you really like adding code, you’ll have to find another solution).
DSE integration
DataStax Enterprise Graph fully integrates with the DataStax Enterprise data platform. This means your DSE
Graph-powered insights can leverage the best of DSE Analytics and DSE Search while remaining always-on
with effortless scale. Say that three times rapidly.
Common Graph Use Cases
DataStax Enterprise Graph is well suited for managing large data sets with numerous and highly
complex relationships. Graph databases make it easy to discover, explore, and make sense of
these relationships. Sorry - it can’t help you make sense of your personal relationships.
Customer 360
Companies want to have a complete view of their users or products.
Understanding every interaction and touchpoint across multiple
business units is key to a great customer experience. A graph model is
the best way to consolidate and make sense of data from disparate
sources such as customer facing apps and business backend systems.
Recommendations
You need to quickly and effectively influence customers to buy
products and recommend them to others. A graph is well suited to
these and similar use cases whether it be for recommending products,
services, next best actions, or advertising based on a user's past
behavior combined with their real-time interactions.
Personalization
A graph database is the most efficient tool for understanding users
and creating insightful, data-driven, real-time experiences. These
actions must be based on the most recent actions and operate in
real time to deliver a highly relevant customer experience.
Fraud Detection
Complex and highly interrelated networks of users, entities,
transactions, events, and interactions bring security risks. A graph
database can help determine which entity, transaction, or
interaction is an outlier, which helps identify breaches, fraud, or
compliance concerns. In short, a graph database helps connect the
dots to identify trends while at the same time spot outliers as
potential threats.
Get started with DSE Graph and the Gremlin Query Language in the free course DS330: DataStax Enterprise Graph
start the course
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DataStax Enterprise is powered by the best distribution of Apache Cassandra™.

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