REPORT
Discover how distributed SQL is evolving to power the next generation of AI applications — without sacrificing resilience, performance, or simplicity.
AI apps don’t look for exact matches — they need semantically similar results, fast. Vector search enables this, but it’s often siloed in specialized vector databases or comes with unacceptable tradeoffs.
Traditional architectures separate vector data from core transactional systems, leading to latency, brittle infrastructure, and compliance risks.
By co-locating vector search with structured data on a distributed SQL platform, CockroachDB uniquely delivers real-time performance with global scale and resilience.
A new generation of AI-driven applications is creating massive new demands on your data architecture. You can’t afford to choose between transactional integrity and AI performance — and now, you don’t have to.
This report explains how vector indexing is being natively integrated into distributed SQL databases, unlocking a unified, scalable foundation for AI chatbots, GenAI Ops, & agentic apps workloads.
This third party report from analyst firm Intellyx explores:
Why AI workloads are breaking conventional data architectures
How vector data changes the rules for indexing, retrieval, and scale
What makes distributed vector indexing uniquely difficult — and how CockroachDB solves it
How co-locating vector and transactional data reduces complexity and boosts accuracy
What real-world use cases look like in retail, banking, and insurance
“Why should data architects sacrifice the resilience, consistency, and scalability of distributed SQL as they move toward AI-native workloads? They don’t have to.”
Andy Kimball
Cockroach Labs Fellow & Vector Indexing Team Lead
Discover how to unify AI and transactional workloads with distributed SQL. Unlock faster insights, enterprise-grade reliability, and lower costs — all on one platform.
Download The New Blueprint for AI-Ready Data.