Title

AWS re:Invent 2022 - Deep dive into Amazon Neptune Serverless (DAT322)

Summary

Speakers: Brad Beebe (General Manager for Amazon Neptune) and Ian Robinson (Principal Graph Architect).
Amazon Neptune Overview: A managed graph database service designed for interactive graph workloads, supporting property graph and RDF graphs with multiple query languages.
Serverless and Global: Neptune now offers serverless and global database capabilities.
Customer Use Cases: Knowledge graphs, identity graphs, fraud detection, and security graphs are among the popular use cases.
New Features: AWS Graph Explorer, Neptune ML with online inductive inferencing, OpenCypher support, and performance improvements.
Neptune Global Database: Supports up to five secondary clusters for disaster recovery and low-latency applications.
Neptune Serverless: Automatically adjusts capacity in response to workload, potentially saving costs compared to provisioning for peak workloads.
Neptune Capacity Unit (NCU): The fundamental unit of serverless capacity, with a minimum and maximum NCU level specified by the user.
Demo: Ian Robinson demonstrated serverless capabilities, including creating a serverless database, setting up a global database, and running a fraud detection workload.
CloudWatch Metrics: Discussed for monitoring serverless scaling and replication lag in global databases.
Resources: Additional sessions, learning materials, and free trials were mentioned for those interested in learning more about Neptune's capabilities.

Graph Database Popularity: Graph databases are gaining traction across various domains due to their ability to innovate using data relationships.
Serverless Benefits: Neptune Serverless can lead to significant cost savings by scaling capacity up or down based on actual workload, avoiding over or under-provisioning.
Graph Database Use Cases: The four highlighted use cases (knowledge graphs, identity graphs, fraud detection, and security graphs) demonstrate the versatility of graph databases in solving complex problems.
OpenCypher and Gremlin: The introduction of OpenCypher provides a declarative way to query graphs, complementing the imperative Gremlin language, catering to different developer preferences.
Performance Improvements: The new data flow engine (DFE) and improvements in variable length path queries indicate AWS's commitment to enhancing Neptune's performance.
Global Database: The Neptune Global Database feature addresses the need for multi-region deployments, which is critical for disaster recovery and reducing latency.
Customer Engagement: The presenters encouraged feedback and engagement from customers, indicating AWS's customer-centric approach to product development.
Graph Explorer: The announcement of the AWS Graph Explorer as an open-source tool reflects AWS's support for community-driven development and broader accessibility to graph database technology.