Umit Catalyurek

Graph computations are a natural way of representing sparse relations and continue to gain attention, especially as knowledge graphs become central to generative AI applications. Can a single engine achieve analytical throughput and transactional consistency without fundamental performance penalties?

In this session, learn about new Amazon Neptune capabilities for high-performance graph analytics and queries over data lakes to unlock the implicit and explicit relationships in your data, driving more accurate, trustworthy generative AI responses.

Amazon Neptune is used by AWS customers to run high-throughput, low-latency graph-based applications with virtually unlimited relationships. In this follow-up demonstration to DAT325, see how the latest Neptune innovations enable next-generation graph-based applications and new use cases.

Learn what’s new with Amazon Neptune, the fully managed graph database service that can store, map, and query relationships between datasets for use in applications like identity and fraud detection.