DataStax Enterprise Graph

A distributed cassandra graph database optimized for enterprise applications - zero downtime, fast traversals at scale, and real-time analysis of complex, related datasets.

Discover the Relationships Between Your Data

Optimized for storing billions of items and their relationships, DSE Graph incorporates all the enterprise-class capabilities of DataStax Enterprise, including continuous availability, linear scalability, advanced security, analytics and full-text search, visual management, visual monitoring and a tools suite for developers.

In short, DSE Graph enables you to identify and analyze hidden relationships between connected data and build powerful modern applications.

Graph Developers

DataStax has many offerings for the graph developer community.

We have programs, tools, and initiatives you can explore including our online education platform DataStax Academy, our work with the Apache Software Foundation and the Apache TinkerPop™ project, graph developer tools like DataStax Studio, and DataStax Developer community initiatives you can subscribe to and check out: bootcamps, meetups, podcasts, and more.

The Gremlin Graph Traversal Machine and Language

The Gremlin Graph Traversal Machine and Language

TinkerPop is an open-source graph computing framework for graph databases and graph analytic systems. It is centered around the Gremlin graph query language, which provides users the ability to express complex graph traversals over their property graphs for both real-time (OLTP) and analytic (OLAP) workloads. Gremlin has support for a variety of programming languages, including Java, Groovy, .NET, JavaScript, and Python, giving users the comfort of working with graphs in their native programming language.

The Practitioner’s Guide to Graph Data

The Practitioner’s Guide to Graph Data

Authors Denise Koessler Gosnell and Matthias Broecheler show data engineers, data scientists, and data analysts how to solve complex problems with graph databases. You’ll learn to:

  • Build an example application architecture with relational and graph technologies
  • Use graph technology to build a Customer 360 application, the most popular graph data pattern today
  • Dive into hierarchical data and troubleshoot a new paradigm that comes from working with graph data
  • Find paths in graph data and learn why your trust in different paths motivates and informs your preferences
  • Use collaborative filtering to design a Netflix-inspired recommendation system



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