WHITEPAPER
This whitepaper shows how industry leaders run AI-adjacent mission-critical systems such as identity access management, metadata management, and vector search on a single distributed SQL database. By leveraging core AI capabilities with distributed SQL, they can eliminate application complexity and simplify global scale without sacrificing speed, security, or consistency.
See how leading AI innovators use the familiar PostgreSQL interface of CockroachDB to massively scale their business-critical use cases.
Most AI architectures bolt together fragmented systems — vector stores, NoSQL, transactional databases, and IAM tools — creating complexity, latency, and risk. This guide shows how CockroachDB unifies these workloads on one distributed SQL platform, eliminating silos while powering global scale and unmatched resilience.
Designed for platform engineers and architects, this whitepaper explores how AI innovators are simplifying complex infrastructure challenges – like IAM, metadata management, and vector search.
Why AI success introduces new infrastructure complexity — and why most stacks can’t keep up
How CockroachDB supports strong consistency, global scale, and low-latency performance for AI use cases
What makes distributed IAM and metadata management so challenging at scale — and how companies like Ory and CoreWeave solved it
How unifying vector and transactional data eliminates operational bottlenecks and stale results
What production-ready architectures look like for AI workloads in real-world environments
CockroachDB powers AI at scale with a familiar PostgreSQL interface, global availability, real-time consistency, and built-in security — no re-architecture and no application complexity when connecting transactional and semantic data.