NetApp federates performance-boosted StorageGRIDs into single namespace for greater scale

NetApp released StorageGRID v12.1, boosting throughput up to 400% and enabling a federated global namespace that scales to 10 exabytes for AI workloads. The update improves security with multi-admin verification and supports AI agents with change tracking, positioning NetApp to compete with MinIO and Cloudian in AI object storage.

NetApp federates performance-boosted StorageGRIDs into single namespace for greater scale NetApp https://www.blocksandfiles.com/flash/2026/05/29/ai-and-all-flash-demand-send-netapp-revenues-to-record-heights/5248292 has sped up its StorageGRID https://www.blocksandfiles.com/ai-ml/2025/09/10/netapp-sends-in-the-clones-to-boost-ai-pitch-as-storagegrid-hits-12/1617718 object storage systems and grouped them into a federated global namespace to provide more scale and simpler management, along with extra security. Enterprise unstructured data kept in object storage form is positioned as a data source for AI large language models and agents. The larger the amount of accessible data in such stores the better, and also the higher the throughput number the better. NetApp’s latest StorageGRID v12. 1 release does more in both regards than the prior v12.0 and also improves security. Sandeep Singh, SVP and GM, Platform at NetApp, said: “As organizations race to turn rapidly growing and distributed volumes of unstructured data into insight and action, they need infrastructure that makes data intelligent, accessible, and ready for AI. With StorageGRID 12.1, NetApp is extending the power of our data platform, giving customers a globally unified namespace to manage data at scale, accelerate AI and analytics workloads, and extract more value from their data wherever it lives.” StorageGRID v12.1 delivers: Global Federated Namespace: Customers can operate at massive scale without rearchitecting applications or workflows with federated namespaces which enable management of multiple globally-distributed StorageGRID systems scaling up to 10 Exabytes in a single namespace. Up to 400 percent higher throughput compared to 12.0 depending on workload and object size. Up to 12 TB/s of throughput to AI Factories. Batch operations allow customers to execute operations on billions of objects. AI agents can track changes to object storage buckets since the last scan, enhancing the ability to build comprehensive AI data pipelines. Expanded security and governance capabilities with stronger controls for regulated environments with multi-admin verification. StorageGRID and caching There is no mention of caching improvements driving faster performance in v12.10. NetApp's competitors make much of their caching technologies. How does their performance and scale compare? StorageGRID has an inner and outer ring architecture; The inner ring offers high speed and low latency, and it is composed of high-performance S3 caches that can deliver near-line-rate performance for working datasets. The inner ring can be connected to a specific GPU cluster. The outer ring provides high capacity, high throughput, and high availability, and it can be connected to multiple GPU clusters simultaneously. In a September 2025 v12.0 StorageGRID blog https://www.netapp.com/blog/storagegrid-12-0-new-features-for-ai-and-modern-apps/ , NetApp said: “S3 remote direct memory access RDMA developments are becoming a clear part of the future of object storage and AI.” NetApp is not yet announcing closer integration with Nvidia for StorageGRID, unlike three object storage competitors. Recently; MinIO https://www.blocksandfiles.com/ai-ml/2026/05/12/minio-adds-petabyte-scale-memkv-cache-for-nvidia-gpu-inference/5238593 built a petabyte-scale MemKV caching system for Nvidia GPUs, effectively sitting atop its AIStor https://www.blocksandfiles.com/ai-ml/2026/02/05/minio-plugs-apache-iceberg-tables-directly-into-aistor/4090411 object storage. Cloudian https://www.blocksandfiles.com/object/2026/06/09/cloudian-closes-gap-between-enterprise-ai-ambitions-and-messy-production-deployments/5252816 updated its HyperScale AIDP https://www.blocksandfiles.com/ai-ml/2025/10/01/cloudian-launches-hyperscale-ai-platform-built-on-nvidia-blackwell-gpus/1592771 turnkey, on-prem appliance with Nvidia blueprint support, native ingestion from file- and object-based storage sources, and data access permission controls. Cloudian is also building in Nvidia STX KV Caching support to its HyperStore product.Scality ADI Autonomous Data Infrastructure https://www.blocksandfiles.com/object/2026/05/12/scalitys-autonomous-data-infrastructure-does-agent-driven-tiering-and-more/5238809 places data in four performance, cost, and protection storage tiers with policy-driven AI agent workers, and S3 over RDMA support. Cloudian, MIniIO, and Scality each support Nvidia’s GPU Direct scheme. The StorageGRID v12.0 blog said caches are complex to deploy, from an infrastructure standpoint. They do not enforce a security model that aligns with the rest of the object storage infrastructure and may not match your organization’s security needs . They are not integrated, from a data consistency perspective, and your end users need to manage cache eviction and time-to-live rules. StorageGRID 12.0 offered “something better” - an integrated cache that enforces security, provides a simple consistency model, and is easy to deploy. Developers get massively accelerated performance right out of the box and the feature works across an ecosystem of S3 applications without any code or infrastructure modifications. Its performance was impressive; As we understand it StorageGRID matches or exceeds Cloudian, MinIO and Scality scale and throughput numbers with the exception of MinIO’s 19.2 TB/s throughput for its AISTor.