Vector Databases (pg_vector) and Real-Time Analytics

This session introduces the basics of vector indexes and vector databases, providing essential knowledge on their use. We will guide you through setting up a Real-Time RAG (Retrieval-Augmented Generation) data pipeline in Kafka and Pinot, a real-time OLAP and vector store. We'll demonstrate how to load documents from a website and perform question-answering on that content. I'll also talk about how AI and Real-Time analytics are converging. Key technical details covered include vector indexes, Apache Pinot, RAG, and creating embeddings for similarity searches. By the end of the session, you will understand how similarity search can be applied in real-time scenarios. This session is ideal for anyone interested in RAG, AI, vector databases, and real-time analytics.