Amazon Neptune: Building Graph Database Applications

Modern data is highly interconnected, yet traditional relational databases often struggle to query deep relationships efficiently. Graph databases solve this by treating relationships as first-class citizens, making them ideal for modern, highly connected applications. In this text-only course, you will transition from a graph database beginner to confidently designing and querying graph architectures. Through clear written explanations, practical code snippets, and structured conceptual exercises, you will master the mechanics of Amazon Neptune. What you'll learn: - Understand foundational graph database concepts, terminology, and the differences between property graphs and RDF. - Query connected data using popular languages like openCypher and Gremlin. - Model real-world use cases including recommendation engines, fraud detection networks, and social graphs. - Configure Amazon Neptune security, including IAM database authentication and encryption. - Apply best practices for graph schema design and query performance optimization. - Integrate Neptune into modern cloud architectures for scalable, real-time applications. You will start with core definitions and graph theory basics before exploring query syntax and architecture patterns. By reading through practical scenarios and analyzing written code examples, you will learn how to build robust connected-data solutions. This course is designed for software developers, data engineers, and system architects new to graph databases. No prior experience with Amazon Neptune or graph query languages is required. Begin reading today to master the fundamentals of graph databases and build smarter, highly connected applications.