Data Modeling: Vector Search for Gen AI Apps
Unlock the power of semantic search with the scalability of Hyper-Converged Database (HCD), the cloud-native enterprise distribution built on Apache Cassandra®. Join us for an in-depth livestream exploring vector search using Storage-Attached Indexing (SAI) in Cassandra — a game-changing capability that brings efficient similarity search to one of the world’s most trusted distributed databases.
In this session, we’ll demystify the fundamentals of vector search and how it enables applications like recommendation engines, image and document retrieval, and natural language search. We’ll show you how Cassandra’s SAI extends beyond traditional indexing to support high-dimensional vector data — without sacrificing performance or scalability.
What’s in it for developers?
You’ll learn how to:
- Store and index vector embeddings in Cassandra using SAI
- Run similarity searches directly on your Cassandra datasets
- Integrate vector search with ML pipelines and AI-powered applications
- Optimize data modeling and query patterns for real-world use cases
Whether you're building AI-enabled apps or modern search experiences, this livestream will give you the knowledge and tools to harness the full potential of vector search on a distributed database you already trust.
Speakers
Erick Ramirez
Developer Advocate
DataStax
Livestream Resources
GitHub Repo - SAI/Vector SearchOptimize Your Apache Cassandra Cluster
Take 30 minutes to improve your open-source Cassandra clusters with a free diagnostic report and debrief discussion with a seasoned Cassandra expert.