Starting a Highly Available Graph Database With Amazon Neptune

Graph databases are becoming very popular. They offer you the possibility to design, handle, and manage data in a graph. That gives you the possibility to manage sets of data of all sizes. There are a lot of use cases where graph databases can be involved, most of them are social networks, fraud detection systems, and recommendation engines. Because of its popularity, there are different solutions you can choose from. AWS is one of the first providers that offer you a Graph DBMS, and this is Amazon Neptune. Neptune is a fast, reliable, and fully managed Graph DBMS that lets you create and manage graph databases. Neptune supports the two common graph models: property graphs and RDF. You can then perform operations using the respective query languages: Gremlin and SPARQL.

In this lab, you will create a subnet group to define in which subnets the Neptune instances (both master and replicas) can be deployed, you will create an Amazon Neptune Database, and you will connect to it and perform some SPARQL operations.

Learning Objectives

Upon completion of this beginner level lab, you will be able to:

• Define subnet groups to associate to an Amazon Neptune Database
• Create a Neptune Graph Database
• Connect to an Amazon Neptune Database and perform some SPARQL commands

Intended Audience

• AWS Certified Big Data Speciality candidates
• Data Engineers who want to build a highly available and secure graph database solution
• Individuals who want to deep dive into the graph databases world

Prerequisites

Basic understanding of high availability and of the Neptune fundamentals is preferred but not required. You can follow the Neptune fundamentals here

Updates

May 23rd, 2022 - Updated the instructions and screenshots to reflect the latest UI