Intro to Graph Databases
|Big Data, Machine Learning, IA & Analytics|
When it’s time to choose the database technology for your app, the choices can be overwhelming. Should you choose SQL or NoSQL? Open source or proprietary? Self-hosted or hosted? If you’re not already familiar with graph databases, you might be tempted to ignore them as an option. But that could be a mistake.
In this hands-on lab, we'll discuss the benefits of graph databases and the basics of how to use one. Then we'll open our laptops and begin coding! We'll explore an existing app that leverages a hosted version of the open-source graph computing framework Apache TinkerPop. We'll discover how we can use APIs and the Gremlin graph traversal language to perform CRUD (create, read, update, and delete) operations. Then we'll write our own code to perform a CRUD operation and explore the graph. Most exciting of all, we'll write code to generate recommendations (one of the biggest strengths of graph databases!) for the app's users.
So bring your laptop with a modern web browser installed, and get ready to graph! You'll leave with an understanding of when you should choose a graph database and how to use one.
Lauren Hayward Schaefer is a software engineer for IBM Cloud Data Services who currently focuses on IBM Graph. Since joining IBM in 2009, Lauren has held a variety of roles including software developer, automation specialist, social media lead, and growth hacking engineer. She holds a BS and MS in Computer Science from North Carolina State University.
Lauren is an international speaker who values authenticity. She is passionate about excellence, empowering and encouraging women, and the color pink.