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Vector Similarity Search in Apache Cassandra®

Presented by

Patrick McFadin, Apache Cassandra Committer and Developer Relations at DataStax

About this talk

Are you struggling with the challenges posed by massive datasets and AI applications? Vector Search is a transformative solution that can help you address these issues. As a decision-maker, you always look for ways to optimize your organization's operations and maximize ROI. Luckily, integrating Vector Similarity Search into Cassandra can help you achieve these goals. Join Patrick McFadin Apache Cassandra Committer and discover how: 1. Vector Search can revolutionize handling AI workloads and managing large datasets. 2. Real-world applications of Vector Similarity Search in content-based image retrieval, recommender systems, and natural language processing. 3. Integrating Vector Similarity Search into Cassandra enables faster and more relevant data retrieval, boosting the performance of data-driven applications. 4. Vector Similarity Search in Cassandra can solve data management challenges, drive efficiencies, and maximize ROI for your organization. Don't miss this opportunity to learn how the cutting-edge Vector Similarity Search functionality in Cassandra can solve your organization's data management challenges, drive efficiencies, and propel your business forward. This strategic move towards enhancing Cassandra's offering underscores its position at the forefront of scalable data management solutions and reaffirms its commitment to meeting the evolving needs of developers and businesses alike.
DataStax

DataStax

3706 subscribers34 talks
Data = AI. DataStax handles Billions of Vectors.
We provide the real-time vector data tools that Gen AI apps need, with seamless integration with developers’ stacks of choice (RAG, Langchain, LlamaIndex, OpenAI, GCP, AWS, Azure, etc).
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