Vector Search + Knowledge Graphs in Oracle AI Database. Using SQL.
KGC 2026
•
1h 26m
https://drive.google.com/file/d/1XdeAYqvcqzoXWKN2ZfA9sbq_yWFm6i2X/view?usp=share_link
https://drive.google.com/file/d/1l5Xd-bOOj7z-IyF-5kOTjVjoO02wQQZm/view?usp=share_link
Oracle AI Database brings AI to your data, with the flexibility of working with multiple data types and data sources (vectors, graphs, spatial, JSON, and more) within a single, unified platform. We will highlight the latest AI capabilities of Oracle AI Database, and in the hands-on lab you will work with vector search and graph queries, both using SQL, making it trivial to work with existing business data while maintaining existing security, governance, and compliance controls. Accompanying hands-on Lab: Link a customer sentiment to the supplier: when a product gets negative reviews, how do you trace the complaint back to the supplier that caused it? Use vector search to identify a sentiment in customer reviews, and then use graph queries to connect the sentiment to the root cause of the complaint by following the product-component-subcomponent-supplier chain. You will see how to create and query graphs in SQL, and how to combine graph traversal with vector search, all without moving data to a special-purpose database. You will see how generative AI can simplify creating a graph and querying a graph, enabling you to specify commands in natural language. You will leave the session with an understanding of how to use vector search and graph queries in Oracle AI Database.
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