Mastering AWS Neptune Analytics: Architecting In-Memory Graph Analytics Solutions with openCypher, Vector Search, and AWS

Unlock the Full Power of Graph Analytics in the AWS Ecosystem

Amazon Neptune Analytics is redefining how businesses leverage complex, connected data. This comprehensive guide shows you how to harness its full potential to power graph-based insights, recommendation systems, network detection, and more—at scale.

Whether you're a cloud architect, developer, or data scientist, this book offers hands-on mastery of AWS Neptune Analytics from fundamentals to advanced querying, vector similarity, and real-time applications.

Inside this Practical Guide, You'll Learn How To:

Build and query high-performance in-memory graph datasets

Use openCypher for powerful graph traversals and analytics

Run built-in graph algorithms (PageRank, WCC, BFS, etc.)

Apply vector search techniques for hybrid AI solutions

Create and load graphs from S3, Neptune DB, and snapshots

Connect via AWS PrivateLink and secure your workloads

Optimize queries and manage Neptune Analytics at scale

Bonus Features:

Real-world use cases for fraud detection, recommendation engines, and cybersecurity

CLI and SDK code examples in Python, JavaScript, and AWS CLI

Best practices for security, performance, and cost-efficiency

If you're looking to gain a competitive edge with graph analytics on AWS, this book is your blueprint.