Why Modern AI Workloads Need Distributed Database Architecture

AI workloads have become essential for businesses, necessitating databases that can handle unpredictable traffic, continuous operation, and global data distribution. Key capabilities for modern AI systems include scalable infrastructure that adapts without manual intervention, continuous evolution without downtime, and high availability during failures. Distributed databases support these requirements by providing elastic scaling, online upgrades, and multi-region failover, ensuring reliable performance and data consistency at scale. They also integrate vector search with operational data to enhance real-time responsiveness, while meeting data residency and governance standards through policy-driven data placement. Additionally, maintaining correctness during concurrent operations and preserving familiar workflows for rapid project deployment are crucial for minimizing operational risk and maximizing innovation velocity. CockroachDB is highlighted as a cloud-native distributed SQL platform that combines these capabilities to support scalable and resilient AI applications, offering solutions for both cloud and self-hosted environments.