Abstract
As enterprises seek to move AI from proof-of-concept to production, standalone vector databases face limits in synchronization, ACID compliance, and resilience. This session shows how PostgreSQL-compatible distributed databases address these issues while keeping a familiar developer experience. Topics include: Building production-ready GenAI applications with distributed SQL, why standalone vector databases create production friction, scaling RAG architectures with pgvector across regions, multi-agent patterns in modern AI, and delivering ultra-resilience for peak traffic, grey failures, and disasters. We'll also dive deep into some critical data-centric design considerations for AI: open standards and flexible foundations, unified data sources, elastic scale requirements, compliance and security for multi-tenant environments, and enterprise reliability.
Software engineers and architects will gain practical strategies for building AI applications that scale globally while delivering the reliability, consistency, and performance enterprise systems demand.
Sponsored session
Session Sponsored By
The modern transactional database for cloud native applications
QCon San Francisco 2025 is a three day conference for senior software engineers, architects and team leads. An international program committee of working engineers selects every session. Patterns and practices, not products and pitches.
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Wednesday 19 November
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