AWS Podcast
#645: Amazon Neptune Analytics
Dec 11, 2023
Dr. Denise Gosnell, Principal Product Manager for Amazon Neptune, discusses the new Neptune Analytics engine and how it helps customers gain insights from large graph databases. The podcast covers various use cases for Amazon Neptune, including fraud detection and targeted content recommendation, as well as the benefits of using Neptune Analytics in generative AI applications. Listeners can also learn how to get started with graph databases and analytics using open source formats and Jupiter notebooks.
18:51
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Quick takeaways
- Amazon Neptune Analytics helps customers analyze graph data from a data lake like Amazon S3 to find insights 80x faster.
- Neptune Analytics supports graph algorithms and vector similarity search, making it useful for complex problems like drug discovery.
Deep dives
Graph Databases: Representing Relationships and Connections
A graph database represents the relationships and connections between data, making it ideal for building applications like social networks. Unlike traditional rows and columns, a graph database is designed to model these relationships, allowing for easier tracking and analysis. Popular use cases for graph databases include knowledge graphs, identity graphs, fraud detection, and security graphs.
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