Gartner predicts that "the application of graph processing and graph databases will grow 100% annually through 2022 to continuously accelerate data preparation and enable more-complex and adaptive data science." The jury is in - performing these sorts of graph algorithms or employing Graph technology is a must-have now for many enterprises. Graph technology, however, remains a relatively young field with many offerings from which to choose. How do you approach selecting from the 15+ Graph vendors, and which features are most important? There is an overwhelming amount of information and complexity. Join us for this webinar as we demystify the complexity and bring clarity to the selection process.
During this webinar, we'll dive into the factors that business and technical leaders should consider when making technology choices for Graph processing and how to apply them for your particular industry and use cases.
KEY LEARNING TOPICS:
- Organizational Readiness: overview of Graph Databases vs NoSQL and SQL; why certain use cases can affect performance and product selection; learn how to differentiate between the different Graph databases
- Graph Product Shoot Out: what specs matter; how to specify speeds-n-feeds in order to measure and compare, and parsing quoted benchmarks and statistics; test & timing; ML & Integration
- Building Enterprise Applications: Graph integration into large complex architecture; data connections; using Graph to visualize your use cases - C360, Fraud Detection, Supply Chain, etc.
- Constructing the Business Case: total cost comparisons; operations and maintenance; tooling and algorithms ecosystems