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When we think of critical data, we often think of payments, health records, identities, etc. However, when it comes to the functionality of business-critical applications, metadata is often the unsung hero. This is becoming even more true in the AI era where organizations are using metadata to turn raw data into strategic assets that fuel sustainable and scalable growth. Metadata provides the context behind AI workloads so that developer teams know where it came from, how it’s been used, and whether or not it's trustworthy.

Cassie McAllister

October 8, 2025

The data landscape has fundamentally shifted: Modern applications demand zero-downtime architectures, while regulatory frameworks expect increasingly precise data locality and residency controls. Meanwhile, AI workloads require continuous access to fresh, consistent data that powers applications at scale.

David Weiss

October 7, 2025

The raw performance of a database starts to matter a whole lot less if that database is down: If you’re fast and you’re down, you’re still down. To be clear, raw performance still matters, but traditional benchmarks don’t measure true customer experience when conditions are less than ideal.

Rob Reid

October 6, 2025

AI systems, from LLM pipelines to generative image models, produce staggering volumes of unstructured data. But it's not the raw objects that cause operational headaches – it's the metadata: versions, references, lifecycles, and access policies. Without metadata management tools built into the database layer, object storage at scale quickly becomes unmanageable.

David Weiss

October 2, 2025

India's technology ecosystem is scaling faster than ever, with remarkable momentum. The country's economy grew at a faster-than-expected 7.8% annual rate in the quarter ending June 2025. Meanwhile, digital commerce alone is projected to quadruple from $160 billion in 2025 to $640 billion by 2035 powered by internet penetration, smartphone adoption, and ambitious government initiatives.

Rob Reid

October 1, 2025

Picture this: Your team has successfully containerized applications, adopted microservices, and migrated to the cloud. Yet somehow, deployments still take hours, scaling remains unpredictable, and that big AI initiative keeps hitting data bottlenecks. 

David Weiss

September 16, 2025

Trusted in production for years by the team at CockroachDB Cloud, the new CockroachDB Operator brings proven automation and operational best practices to your Kubernetes deployments.

Michael Wang

September 10, 2025

Unlike traditional relational databases, CockroachDB's distributed architecture requires new approaches to deployment topologies, schema design, performance tuning, monitoring, and operational best practices. CockroachDB delivers global scale, zero-downtime operations, and strong consistency. However, teams often hit a roadblock: the learning curve.

David Weiss

September 4, 2025

Every AI application – whether it's an LLM-powered chatbot, an API platform, or a generative service – depends on a secure, always-on identity layer. IAM (identity access management) determines who gets access, what they can do, and how long their session lasts. When the database behind IAM fails, so does the AI experience.

David Weiss

September 3, 2025