Behind the hype: managing billion-scale embeddings in Elasticsearch and OpenSearch
Conference (INTERMEDIATE level)
Room B
Semantic search is often hailed as a game-changer, promising to solve challenges like relevance, complex sentence analysis, and synonym detection with just a few embeddings and a machine learning model. The demos look impressive—but what happens when you're dealing with more than a billion embeddings?
In this talk, we move past the hype to explore the real-world complexities of managing large-scale vector databases, focusing on Elasticsearch and OpenSearch. Through practical, hands-on examples, we’ll share proven strategies to ensure scalability, maintain high performance, and optimize costs. Whether you're already managing a billion-vector database or preparing for large-scale deployment, this session will equip you with the knowledge and tools to tackle real-world challenges effectively.
In this talk, we move past the hype to explore the real-world complexities of managing large-scale vector databases, focusing on Elasticsearch and OpenSearch. Through practical, hands-on examples, we’ll share proven strategies to ensure scalability, maintain high performance, and optimize costs. Whether you're already managing a billion-vector database or preparing for large-scale deployment, this session will equip you with the knowledge and tools to tackle real-world challenges effectively.