Scaling AI Frontiers: Building Production-Ready RAG Applications with PG Vector on PostgreSQL
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The rise of Generative AI has made Retrieval-Augmented Generation (RAG) a cornerstone for building intelligent, context-aware applications. While many solutions turn to specialized vector databases, this often introduces architectural complexity, data silos, and new operational overhead. What if you could build highly scalable, enterprise-grade RAG applications using the trusted, powerful, and familiar environment of PostgreSQL?
This talk provides a comprehensive blueprint for leveraging PostgreSQL as a complete solution for RAG workloads. We will dive deep into the pg_vector extension, demonstrating how it transforms PostgreSQL into a first-class vector database capable of storing and efficiently querying millions of embeddings alongside your transactional data.
Join us to explore a practical, production-focused approach that goes beyond simple proofs-of-concept. We will showcase a powerful database toolkit designed to streamline development, management, and scaling. Furthermore, we will detail how to deploy these sophisticated AI applications on Multi-Cloud Platform (MCP) Servers, ensuring high availability, robust performance, and seamless management.
Attendees will leave with:
A clear understanding of how to implement RAG architecture within PostgreSQL.
Actionable insights into using pg_vector for high-performance similarity searches.
A repeatable strategy for managing and scaling their database infrastructure using a dedicated toolkit.
A deployment blueprint for running these workloads reliably on MCP Servers.
This session is for developers, DBAs, and architects looking to simplify their AI stack without sacrificing performance or scalability. Discover how to turn your existing PostgreSQL expertise into a superpower for the new age of AI.
- Date:
- 2025 October 17 13:20 +11
- Duration:
- 40 min
- Room:
- Oxford I + II
- Conference:
- PG Down Under 2025
- Language:
- Track:
- Development
- Difficulty:
- Hard