Data Management Glossary
NetApp AI Data Engine (AIDE)
What is the NetApp AI Data Engine?
The NetApp AI Data Engine (AIDE) is a data discovery, curation, and AI data preparation layer from NetApp, introduced in October 2025 alongside the NetApp AFX disaggregated storage platform. AIDE builds a metadata catalog of data on NetApp storage, keeps AI pipelines synchronized with source data, classifies sensitive information, and prepares data for retrieval by generating vector embeddings. It is based on the NVIDIA AI Data Platform reference design.
Source: SiliconANGLE
AIDE Components
- Metadata Engine. Generates a structured, queryable view of the NetApp data estate.
- Data Sync. Uses SnapMirror and automatic change detection to keep data sent to AI pipelines current and reduce redundant copies.
- Data Guardrails. Scans and classifies data continuously, identifies sensitive information, and applies automated handling policies.
- Data Curator. Handles discovery, vectorization, and retrieval, integrating NVIDIA NIM microservices for embedding.
Source: Blocks and Files
Where AIDE Runs
AIDE launched on the NetApp AFX platform, which separates ONTAP storage controllers from capacity. AIDE services run on DX50 data compute nodes, which pair an AMD processor with an NVIDIA L4 GPU so metadata and AI processing do not load the primary storage controllers. NetApp also announced support for NVIDIA RTX Pro servers.
At NetApp Insight 2026, NetApp said AIDE will extend discovery across ONTAP, StorageGRID, and non-NetApp storage, discovering and characterizing data in NFS, SMB, and S3 repositories. Upcoming capabilities include AI-generated data understanding, governance intelligence, and analytics integrations.
Source: Blocks and Files
Why AIDE Matters for Unstructured Data
NetApp AIDE reflects a broad shift: primary storage vendors now are promoting data intelligence and AI data preparation, not only capacity and performance. The reason is unstructured data. Files and objects make up 80% to 90% of enterprise data, they carry no schema, and they are the raw material for retrieval-augmented generation, agents, and model training. Whoever indexes and curates that data controls the first step of every enterprise AI pipeline.
AIDE was introduced in October 2025 on new hardware, and its reach beyond NetApp storage was announced in September 2026 as an upcoming capability. For an organization that runs most of its file data on ONTAP and has invested in AFX, AIDE promises to bring discovery and vectorization close to that data. Most enterprises, however, run unstructured data across several storage vendors and clouds, and they need answers today, not after the next platform cycle. Four questions decide whether a storage-vendor data engine covers the whole problem:
- Coverage. Was it designed to index every storage system equally, or its own platform first, with other vendors added later?
- Action. Once data is found, can it be tiered, migrated, copied, or deleted on any storage, or only within the vendor ecosystem?
- Cost. Does it require new storage or compute appliances before it delivers any insight?
- Maturity. Is it proven in production at enterprise scale across mixed storage, or still rolling out?
The Cost of Staying Inside One Vendor
Two forces make the platform question more expensive in 2026 than at any point in the last decade: flash prices and lock-in.
Memflation Raises the Price of Every Flash Terabyte
AI infrastructure demand is absorbing memory and NAND supply. TrendForce forecast enterprise SSD prices would rise 53% to 58% quarter over quarter in the first quarter of 2026, a record quarterly increase, and projects NAND flash contract prices to rise another 15% to 20% in the fourth quarter of 2026. Gartner estimates a 130% increase in combined DRAM and SSD prices by the end of 2026.
AIDE launched on AFX, an all-flash platform, with GPU-equipped data compute nodes. A path to AI data preparation that starts with new all-flash hardware is the most price-exposed path available right now. Meanwhile about 70% of unstructured data on primary storage is typically cold, which means most of the flash an organization already owns holds data that does not need flash at all.
Lock-In Compounds With Every Terabyte Prepared Inside One Ecosystem
- Insight stays on the platform. Metadata, classifications, and AI pipelines built inside a vendor data engine live on that vendor’s infrastructure. Changing or adding vendors means rebuilding them.
- Block tiering creates a rehydration penalty. ONTAP FabricPool tiers cold blocks, not files, to object storage. Tiered data is not readable as files at the destination, so moving it off NetApp requires rehydrating it back through ONTAP first, consuming the same expensive primary capacity the tiering was meant to free.
- Every refresh repeats the bill. When the data engine requires the vendor’s latest platform, getting AI-ready data becomes a reason to buy more of the same flash at the next refresh.
The more data an organization prepares for AI inside one vendor, the harder that vendor is to leave and the more each refresh costs.
How Komprise Changes the Math
- Reclaim flash before buying more. The Komprise Flash Stretch Assessment analyzes unstructured data across multi-vendor storage, including ONTAP, and identifies how to reclaim up to 70% of primary storage capacity. At current prices, reclaiming 70%+ of primary flash capacity is worth more than $350,000 per petabyte.
- Tier files, not blocks. Transparent Move Technology tiers whole files to any object or cloud target. Users keep accessing them from the original location, tiered files are readable natively at the destination, and there is no rehydration penalty for access or migration. TMT cuts 70%+ of storage costs.
- Keep the insight portable. The Global Metadatabase, tags, and policies live in Komprise, independent of any array, and carry over when storage changes.
Why Komprise Is Built for Heterogeneous Storage at Scale
Komprise was built from the start for the environment enterprises actually run: many storage vendors, many clouds, and petabytes of file and object data that keep growing. Why Komprise?
- Proven at scale. Komprise manages more than one exabyte of enterprise data across healthcare, life sciences, financial services, media, and public sector organizations. Learn more about the Komprise architecture.
- Heterogeneous by design. Komprise uses open standards to work with storage and cloud platforms, including NetApp, Dell, Everpure, Qumulo, VAST Data, HPE, IBM, Nutanix, Scality, Cloudian, Wasabi, AWS, Microsoft Azure, and Google Cloud. No platform is a second-class citizen. See integrations.
- No hardware to buy. Komprise is agentless, scale-out software that deploys in minutes and requires no agents on the storage. Insight does not depend on a storage purchase.
- Insight and action, across vendors. The Komprise Global Metadatabase indexes all storage, and Komprise acts on that index everywhere: tier, migrate, copy, confine, or deliver to AI.
- Independent of any one vendor. The index, tags, and policies live in Komprise, not on an array. They carry over when storage changes, which keeps refresh and vendor decisions in the customer’s hands.
How Komprise Works With NetApp Storage
Komprise treats NetApp ONTAP as one of many sources and targets, alongside every other storage system in the estate.
- Index. Komprise indexes file and object metadata across ONTAP, other NAS platforms such as Dell PowerScale and Everpure, object storage, and cloud storage into the Komprise Global Metadatabase.
- Find and classify. Deep Analytics queries the index by age, owner, type, and tags, and Smart Data Workflows run PII detection and tagging.
- Act on any storage. Transparent Move Technology tiers cold ONTAP files at the file level with no rehydration penalty and cuts 70%+ of storage costs. Elastic Data Migration moves data to or from ONTAP with 27X faster NFS migrations, and Komprise Hypertransfer delivers 25X faster SMB migrations.
- Curate and deliver to AI. Komprise Intelligent AI Ingest delivers curated, governed data sets from every silo to any AI stack with 2X faster data flows.
AI Agent Access With Komprise Universal File MCP
AI agents need more than a vector index of one vendor’s storage. They need to search enterprise files wherever they live, respect file permissions, and avoid loading irrelevant content into the context window.
Komprise Universal File MCP gives AI agents one Model Context Protocol interface to file and object data across every storage silo, including NetApp and non-NetApp systems. It is built on the Komprise Global Metadatabase, which applies a consistent schema to every file. Agents query metadata first and load full files only when needed, and Deep Analytics filters out irrelevant, outdated, conflicting, and duplicate files before they reach the model. Every query runs under the requesting user’s existing access permissions, so a response never includes data that user is not authorized to see. Agents also reach tiered and archived data directly, with no rehydration. One universal MCP replaces a stack of storage-specific connectors and the MCP bloat they create.
AIDE prepares data for AI on NetApp infrastructure. Komprise manages and delivers unstructured data across all storage, including NetApp, and is already doing it at exabyte scale.
| Evaluation Criteria | NetApp AI Data Engine (AIDE) | Komprise |
|---|---|---|
| Design center | AI data preparation on NetApp infrastructure | Unstructured data management for heterogeneous storage, by design |
| Maturity | Introduced October 2025; cross-vendor discovery announced as upcoming in September 2026 | In production at enterprise scale; manages more than one exabyte of enterprise data |
| Storage coverage | NetApp first; non-NetApp NFS, SMB, and S3 discovery on the roadmap | 15+ storage and cloud platforms, including ONTAP, indexed equally in the Global Metadatabase |
| Infrastructure required | AFX all-flash platform with GPU-equipped DX50 data compute nodes | Agentless, scale-out software; no storage or compute appliance purchase |
| Flash price exposure | Starts with new all-flash hardware at record 2026 flash prices | Flash Stretch Assessment reclaims up to 70% of primary flash before any purchase |
| Cold data and cost | Not the primary focus | Transparent Move Technology tiers cold files, cuts 70%+ of storage costs |
| Tiering method | ONTAP FabricPool tiers blocks; tiered data not readable as files at the destination | Whole files tiered to any object or cloud target, readable natively |
| Rehydration penalty | Tiered data must return through ONTAP before it moves off NetApp | None for access or migration |
| Migration | Within the NetApp ecosystem | Elastic Data Migration, 27X faster NFS; Komprise Hypertransfer, 25X faster SMB, to or from any vendor |
| Discovery and classification | Metadata Engine and Data Guardrails | Deep Analytics and Smart Data Workflows with PII detection |
| AI data delivery | Data Curator with NVIDIA NIM vectorization | Komprise Intelligent AI Ingest, 2X faster data flows to any AI stack |
| AI agent access | Tied to the NetApp data estate | Komprise Universal File MCP: one permission-aware MCP interface across all storage |
| Lock-in | Metadata, pipelines, and tiered data all bound to NetApp infrastructure | Index, tags, and policies portable; carry over when storage changes |
NetApp AIDE FAQ
What is the NetApp AI Data Engine?
The NetApp AI Data Engine (AIDE) is a NetApp software layer that catalogs, synchronizes, classifies, and vectorizes data on NetApp storage to prepare it for AI. It launched in October 2025 with the NetApp AFX platform and is based on the NVIDIA AI Data Platform reference design.
What are the components of NetApp AIDE?
AIDE has four components: a Metadata Engine that builds a queryable view of the data estate, Data Sync that keeps AI pipelines current using SnapMirror and change detection, Data Guardrails that classify sensitive data and apply policies, and a Data Curator that handles discovery, vectorization, and retrieval.
Does NetApp AIDE require AFX?
AIDE launched on the AFX platform and runs its services on DX50 data compute nodes with NVIDIA GPUs. NetApp has also announced support for NVIDIA RTX Pro servers. Check current NetApp documentation for supported configurations.
Does NetApp AIDE work with non-NetApp storage?
At NetApp Insight 2026 in September 2026, NetApp announced that AIDE will extend discovery to non-NetApp NFS, SMB, and S3 storage, along with ONTAP and StorageGRID. The initial release focused on NetApp storage.
What is the difference between NetApp AIDE and Komprise?
AIDE is a NetApp data engine introduced in October 2025, built around NetApp AFX and ONTAP infrastructure, with support for other storage announced as upcoming. Komprise was designed for heterogeneous storage from the start and manages more than one exabyte of enterprise data across 15+ storage and cloud platforms, including ONTAP. It is agentless software with no appliance to buy, and it acts on data across every vendor: tiering, migration, AI data delivery, and AI agent access through Komprise Universal File MCP.
Is NetApp AIDE proven at enterprise scale across multi-vendor storage?
AIDE launched in October 2025 on NetApp AFX, and NetApp announced discovery of non-NetApp storage in September 2026 as an upcoming capability. Organizations that need cross-vendor data intelligence and AI data preparation in production today use storage-independent software such as Komprise, which manages more than one exabyte of enterprise data across mixed storage.
How do AI agents access data on NetApp and other storage?
Komprise Universal File MCP gives AI agents one Model Context Protocol interface to file and object data across NetApp, other NAS vendors, object storage, and cloud. Every query runs under the requesting user’s existing access permissions, agents load metadata before full files to reduce token use, and tiered or archived data is reachable with no rehydration.
Does NetApp AIDE create vendor lock-in?
AIDE keeps metadata, classifications, and AI pipelines on NetApp infrastructure, and it launched on the NetApp AFX platform. Combined with ONTAP FabricPool block tiering, which requires tiered data to be rehydrated through ONTAP before it moves elsewhere, preparing data for AI inside AIDE deepens dependence on NetApp. Storage-independent software such as Komprise keeps the index and policies portable and tiers whole files with no rehydration penalty.
How do rising flash prices affect a NetApp AFX and AIDE investment?
AFX is all-flash, and TrendForce forecast a record 53% to 58% quarter-over-quarter rise in enterprise SSD prices in the first quarter of 2026. Before buying new flash for AI data preparation, assess how much existing ONTAP capacity holds cold data. The Komprise Flash Stretch Assessment identifies how to reclaim up to 70% of primary storage capacity, worth more than $350,000 per petabyte of flash at current prices.
What is the rehydration penalty with NetApp FabricPool?
FabricPool tiers cold ONTAP blocks to object storage. Because the tiered data is blocks, not files, it is not readable at the destination and must be rehydrated back through ONTAP before it is migrated or accessed outside NetApp. Komprise Transparent Move Technology tiers whole files instead, so tiered data stays readable at the destination and there is no rehydration penalty.
Can you use Komprise with NetApp ONTAP?
Yes. Komprise indexes ONTAP file data alongside other storage, tiers cold ONTAP files to lower-cost object or cloud storage with Transparent Move Technology, and migrates data to or from ONTAP with Elastic Data Migration. See the NetApp FabricPool glossary page for how file-level tiering differs from ONTAP block tiering.
Which layer of the AI data platform does NetApp AIDE address?
AIDE spans layer 2, Metadata and Discovery, through layer 4, Enrichment and Curation, for data on NetApp infrastructure, with vectorization reaching into layer 5, AI Delivery and Consumption. Komprise operates at layers 2 through 4 across all storage. See the AI Data Platform glossary page.