WHITEPAPER

Three AI Use Cases, One Database:

IAM, Metadata Management, and Vector Search at Scale

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.

Inside the Whitepaper

See how leading AI innovators use the familiar PostgreSQL interface of CockroachDB to massively scale their business-critical use cases.

Identity access management

Identity & Access Management (IAM)

Learn how Ory powers resilient identity management for OpenAI – backed by CockroachDB to support 400 million weekly active users with strong consistency, elastic scaling, and zero downtime.
Metadata management

Metadata Management for AI Object Storage

See how CoreWeave manages trillions of metadata entries with trusted PostgreSQL tools, strong consistency, and low-latency performance across global AI workloads.
Vector

Real-Time Vector Search

Discover how applications scale globally and stay resilient by joining vector and transactional data in one SQL query – eliminating sync delays, stale results, and separate vector stores.
Vector search vs. traditional search

The New Challenge of Scaling AI Infrastructure

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.

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What You’ll Learn

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

Run AI workloads without limits on distributed SQL

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.