NetApp StorageGRID Was Built for Cold Data

Most companies are paying for two storage tiers for training one AI model. Your AI models are only as good as the data you can feed them and how fast you can feed it. The last thing your pipeline needs is a storage tier designed for data nobody's using.

That's the product NetApp built. A place to park the data ONTAP is done with. A cloud tier with a 31-day cooling period. A capacity play for data nobody's accessing.

Don't take our word for it. NetApp's own documentation makes the case for us. Their docs say "tier inactive, cold data to StorageGRID." Their product page promotes "long-term data retention and backup." Their technical reports call object storage "generally less performative than file or block."

Is that where you want your AI training data, your Iceberg tables, your model checkpoints? At MinIO we believe AI Storage is Object Storage and we have the performance claims to back it up. AIStor delivers 19.2 TiB/s read throughput at exabyte scale while StorageGRID is still waiting for data to go cold.

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Let us show you the difference and how much you can save with a smaller footprint.

What You Get When You Switch to AIStor

GPU-Ready

GPUDirect® RDMA for S3-Compatible Storage

Native Iceberg

AIStor Tables. Built-In Catalog REST API. No Add-Ons.

Radical Simplicity

Single Binary. No Cassandra.

Up to 40% Less

Total Cost vs Proprietary

AIStor Was Built for Analytics, Lakehouse, and AI.

S3 API Compatibility
AI & Lakehouse Performance
Operational Simplicity
TCO
Architecture & Design
FAQs

S3 API Compatibility

MinIO’s AIStor is built for Modern AI
NetApp StorageGRID
Legacy Architecture
Native S3 API. Every call, every SDK, every tool—just works.
S3 API Version 2006-03-01 “with support for most operations, and with some limitations” per NetApp’s own docs.
Full compatibility with AWS S3 SDKs across all languages. Drop-in replacement for Amazon S3.
NetApp docs state bucket, object, and multipart operations are “implemented differently than the Amazon S3 REST API.”
S3, S3 Express, Iceberg Catalog REST API, SFTP, and MCP protocols. All native, no gateways.
Having more than 100 active tenants “can result in slower S3 client performance” per NetApp’s own documentation.
IAM-compatible policies and STS for identity federation. Multi-LDAP. Per-tenant isolation.
IAM is “a subset of the S3 REST API policy language.” STS AssumeRole only added in 12.0. No OIDC. No multi-LDAP.
No tenant-count scaling wall. Performance holds whether you have 10 tenants or 10,000.
Application modifications often required. Developers must “understand the implementation details” before integrating.
Why It Matters: Legacy S3 gaps slow every integration; AIStor’s native compatibility lets your teams ship without workarounds.

AI & Lakehouse Performance

MinIO’s AIStor is built for Modern AI
NetApp StorageGRID
Legacy Architecture
Built for AI. 19.2 TiB/s reads at exabyte scale. Native Iceberg. No bottlenecks.
Traditional object storage retrofitted with a caching layer for AI workloads.
19.2 TiB/s read throughput at 1 EiB (ExaPOD reference architecture, 640 servers). Linearly scalable. Published, reproducible.
Claims “up to 20x more throughput than before” relative to own prior version. No absolute GB/s numbers published.
Native Apache Iceberg V3 Catalog REST API. AIStor Tables is GA, built into the data store, no extra cost.
No native Iceberg. Lakehouse requires deploying and licensing Dremio separately.
NVIDIA GPUDirect® RDMA for S3-Compatible Storage. Direct storage-to-GPU memory path. ~5x throughput gains.
No S3 over RDMA. No GPUDirect integration. GPU clusters access data via standard TCP/IP stack.
AIHub (HuggingFace-compatible model repo), promptObject (LLM query API), native Delta Sharing with Databricks.
No model repository. No inference APIs. No Delta Sharing. AI story is a partnership story, not a product story.
Why It Matters: The fastest path from storage to GPU is the one with nothing in between. That’s AIStor.

Operational Simplicity

MinIO’s AIStor is built for Modern AI
NetApp StorageGRID
Legacy Architecture
Single binary. No external dependencies. No Cassandra. No Zookeeper. Deploy in minutes.
Multiple node types (Admin, Gateway, Storage) with distinct operational requirements.
Zero-downtime rolling upgrades. Add capacity on the fly. No rebalancing, no resharding.
PeerSpot reviewers: “beyond the initial setup, this product is a little bit difficult to configure.”
Kubernetes-native: full Operator, DirectPV CSI driver, Helm charts. Cloud-native from day one.
NetApp KB documents: S3 timeouts after upgrades, high CPU across nodes, Cassandra timeout exceptions on PUTs.
Self-healing at every layer. Drives, nodes, racks, sites. Non-blocking healing preserves foreground I/O.
Not Kubernetes-native. Deploys on VMs, Docker, or appliances. No Operator of comparable scope.
OpenTelemetry + eBPF observability. Prometheus-native metrics. Full operational visibility.
Observability via Grid Manager + AutoSupport. Full ecosystem visibility requires NetApp BlueXP.
Why It Matters: Free up operational resources and deliver more reliable solutions to your business faster.

Total Cost of Ownership

MinIO’s AIStor is built for Modern AI
NetApp StorageGRID
Legacy Architecture
Up to 40% lower TCO than proprietary AI storage vendors. No lock-in, no hardware markups.
Enterprise pricing with appliance-centric economics. PeerSpot users call pricing “not competitive.”
Software-only. Run on any commodity hardware, any vendor, any generation. No forced refresh cycles.
Appliance-centric model means hardware procurement cycles, vendor-locked refresh timelines, and spare parts inventory.
Capacity-based subscription. No per-operation, access, or egress fees. Predictable billing.
Add Dremio licensing for lakehouse. Add ONTAP for full data management. Cost stacks up.
All features included. Tables, AIHub, Cache, Firewall, KMS. No per-feature or per-seat licensing.
ONTAP tiering positions StorageGRID as cold tier. You’re buying two storage systems.
One product to learn, deploy, operate. Your existing DevOps team runs it. No specialists required.
PeerSpot: “NetApp is known for not being the cheapest storage option, which is also valid for StorageGRID.”
Why It Matters: Hardware lock-in, add-on licensing, and vendor-controlled refresh cycles are where legacy margins hide. AIStor’s software-only model has nowhere to hide them.

Architecture & Design

MinIO’s AIStor is built for Modern AI
NetApp StorageGRID
Legacy Architecture
Stateless. No metadata database. Metadata stored atomically with each object. Nothing between you and your data.
Apache Cassandra-based metadata store. Separate Admin, Gateway, and Storage node types.
Single-tier scale-out. No gateways. No protocol translation. Native S3 end to end.
NetApp KB documents Cassandra timeout exceptions causing HTTP 503 on S3 PUT requests at scale.
Go + SIMD-optimized assembly (AVX512, NEON, VSX) for erasure coding, encryption, and hashing.
Part of multi-protocol portfolio alongside ONTAP (block/file). ONTAP-to-StorageGRID tiering positions it as cold tier.
Inline erasure coding + bitrot detection. No SAN. No NAS. No POSIX. Purpose-built for objects.
One trillion object limit per cluster (doubled in 12.0). Inner/outer ring caching adds architectural complexity.
Flat namespace to exabytes. Performance scales linearly. Double the nodes, double the throughput.
E-Series SANtricity hardware heritage. ILM policy engine adds operational overhead for placement decisions.
Why It Matters: Every Cassandra timeout, every ILM misconfiguration, and every gateway failover is a consequence of architectural complexity. AIStor was designed to have none of those consequences.

Frequently Asked Questions

Can MinIO really replace our NetApp StorageGRID deployment?

Yes. AIStor provides complete S3 API compatibility, meaning any application that works with StorageGRID’s S3 interface will work with AIStor without modification. Many organizations have migrated petabytes from legacy object stores while applications continued running unchanged. Because StorageGRID’s own S3 implementation has documented limitations, some applications may actually work better with AIStor’s more complete S3 API.

How does AIStor performance compare for AI training workloads?

AIStor is purpose-built for AI/ML throughput and latency. The ExaPOD reference architecture delivers 19.2 TiB/s read throughput at 1 EiB, scaling linearly across 640 servers. AIStor also supports GPUDirect® RDMA for S3-Compatible Storage, providing a direct storage-to-GPU memory path that StorageGRID cannot match. StorageGRID 12.0 claims “up to 20x” improvement, but that’s relative to their own prior version, and no absolute numbers are published for comparison.

What about enterprise features like encryption, replication, and compliance?

AIStor includes enterprise-grade security as standard, not add-ons: FIPS 140-3 compliant encryption, built-in Key Management Server, active-active replication, erasure coding with bitrot healing, IAM policies, S3 Object Lock, and a purpose-built data firewall. AIStor has been assessed “Awardable” for Department of Defense work in the CDAO’s Tradewinds Marketplace. All included at every subscription tier. No per-feature licensing.

StorageGRID 12.0 has a new caching layer. Doesn’t that close the performance gap?

StorageGRID 12.0’s caching layer is meaningful, delivering “up to 10x the performance of current appliances” per NetApp. But a cache is a workaround for an underlying architectural limitation. AIStor doesn’t need a caching workaround: DRAM-based distributed caching is built in, metadata is stored atomically with objects (no Cassandra overhead), and Go + SIMD assembly delivers near-hardware-line-rate throughput natively. The architectural gap remains.

We need Apache Iceberg for our lakehouse. How do the two compare?

This is one of the sharpest differentiators. AIStor Tables provides a native Apache Iceberg V3 Catalog REST API built directly into the data store, the first in the industry. Iceberg tables are first-class citizens with views, multi-table transactions, and no additional software. Included at no extra cost. Want to add Dremio, Trino, or Spark? AIStor works with all of them. The difference is that with AIStor, an external platform is a choice. With StorageGRID, which has no native Iceberg, it’s a prerequisite and an added cost before you can write your first table.

Is AIStor suitable for large enterprise deployments?

Absolutely. AIStor runs in production at many of the world’s largest enterprises, serving exabytes of data. The company recorded multiple eight-figure, exabyte-scale customer deals in 2024. AIStor scales horizontally without limit within a single flat namespace. With over 2 billion Docker pulls and 50,000+ GitHub stars, it’s the most widely deployed object store in the world.

Why Teams Choose AIStor

The world's most demanding AI workloads run on AIStor. Here's why.
Unmatched Efficiency
Get 4x object store performance with a smaller footprint and big savings.
check-circle-broken
True S3 Compatibility
Every SDK. Every tool. Every framework. No “with some limitations” footnotes. It just works.
Deploy Anywhere
One binary runs everywhere. Cloud, colo, edge, air-gapped. No appliance dependencies.
Enterprise Security
FIPS 140-3. Built-in KMS. Data Firewall. IAM. Object Lock. Security built in, not bolted on.
bar-chart-12
Linear Scale
Add nodes, add performance. Exabyte namespace. No architecture redesign required.
Radical Simplicity
No specialists. No professional services. No Cassandra to tune. Your team can run this.

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