Data Management Glossary
VNA
What Is a VNA?
A Vendor Neutral Archive (VNA) is a medical imaging storage architecture that stores DICOM images and related clinical content in a vendor-independent format, making them accessible and portable regardless of which PACS vendor, modality, or clinical application originally generated them. Unlike proprietary PACS storage that ties imaging data to a specific vendor’s file system and software, a VNA stores images in standard DICOM format with open APIs, ensuring that studies archived under one system remain accessible after a PACS replacement without requiring a full data migration. A VNA removes vendor dependency by storing images in open formats, making them accessible regardless of which PACS imaging software generated them.
The case for a vendor neutral archive is made the same way by every vendor that sells one: eliminate vendor lock-in, reduce storage costs, enable cross-department access, integrate images into the EHR, and prepare your archive for AI. While these claims are consistent across vendors, the practical implementation — and the gaps that remain — vary significantly.
Why VNA Matters for Storage Costs and AI
VNA addresses the storage lock-in problem that has plagued healthcare IT for decades, but it does not by itself solve the data management, cost optimization, and AI readiness challenges that modern health systems face. Those require a data management layer above the VNA:
- Storage independence — a VNA core stores patient data in standard DICOM native format, ensuring true data sovereignty and allowing the cloud PACS to scale instantly using geo-redundant cloud storage protocols, protecting against ransomware and hardware failure; this is a significant improvement over proprietary PACS storage but still requires active lifecycle management to control costs
- Multi-modality consolidation — VNA centralizes imaging data from radiology, cardiology, pathology, ophthalmology, and other departments into a single archive, eliminating the data silos that make cross-departmental AI initiatives impossible; a VNA provides access to both structured and unstructured data with metadata tagging of unstructured data for searchability and meaningful clinical context, as well as the scalability to serve multi-site installations
- AI preparation gap — VNA solves the storage format problem but does not solve the AI data preparation problem; finding specific imaging datasets across petabyte-scale VNA archives, enriching DICOM metadata for AI queries, filtering PHI before AI ingestion, and delivering curated datasets to AI pipelines requires a data management layer that most VNA systems do not provide natively
- Cost management gap — VNA reduces lock-in but does not automatically optimize storage costs; without active lifecycle management and intelligent tiering, VNA archives accumulate cold studies on expensive storage tiers just as legacy PACS did, particularly as flash and NAND prices rise 130% by end of 2026, according to Gartner
VNA and the Komprise Data Management Layer
Komprise works alongside any VNA as an independent unstructured data management layer that provides the visibility, lifecycle management, AI data preparation, and governance capabilities that VNA systems themselves do not provide. This is the combination that leading health systems are deploying to address both the cost crisis and the AI opportunity simultaneously:
- Cross-silo visibility including VNA — the Komprise Global Metadatabase indexes all content stored in the VNA alongside PACS, NAS, and cloud object storage, providing a unified view of the imaging estate with file age, modality, access patterns, PHI status, and custom DICOM header attributes across all repositories from a single interface
- Intelligent lifecycle management for VNA content — Komprise identifies cold studies in VNA archives that have not been accessed since the initial diagnostic period and creates policies to tier them to lower-cost object storage transparently; VNA access patterns and PACS retrieval workflows are completely unaffected
- KAPPA for VNA metadata enrichment — KAPPA data services extract custom DICOM header attributes from studies stored in the VNA at petabyte scale using serverless processing, writing enriched metadata back to the Global Metadatabase; this makes VNA content precisely queryable for AI data preparation without requiring any changes to VNA configuration or access patterns
- AI data curation from VNA — Smart Data Workflows are automated and Deep Analytics queries the enriched Global Metadatabase to identify exactly the right studies from the VNA for a given AI use case; a clinical AI team can find all whole-slide pathology images for pancreatic cancer studies from the last five years across a 10PB VNA archive in a single query, then deliver those specific studies to an AI pipeline without moving the full archive
- PHI governance across VNA and cloud — Komprise Sensitive Data Management scans VNA content for PHI before any data reaches AI pipelines or cloud analytics platforms; de-identification policies, exclusion rules, and audit trails are enforced consistently across VNA, PACS, and cloud storage from a single governance framework
- VNA migration without disruption — Komprise Elastic Data Migration moves content between VNA vendors, from on-premises VNA to cloud-native VNA, or from legacy proprietary archives to modern open-format VNA systems up to 27x faster than standard tools with full DICOM metadata fidelity; Komprise Hypertransfer delivers 25x faster performance over WAN for large-scale VNA migrations between data centers and cloud destinations
Learn more about Komprise for Healthcare
How VNA Differs from DICOM and PACS
VNA is the storage independence layer that sits between PACS clinical applications and the underlying NAS or cloud storage infrastructure. It is the solution to the vendor lock-in problem that proprietary PACS storage created:
- VNA vs PACS — a VNA allows medical images received from several devices, modalities, and locations to be viewed and stored in a collaborative manner; unlike a PACS, images can be stored using a standard interface enabling access via any workstation regardless of vendor; PACS is optimized for clinical workflow, VNA is optimized for long-term storage and portability Dell EMC
- VNA vs DICOM — DICOM is the standard VNA uses to store files in open format; VNA is the system that enforces DICOM compliance and vendor neutrality across any PACS or modality that writes to it
The key VNA differentiator — a VNA normalizes all proprietary metadata elements that have been systematically introduced into image headers by various PACS, resulting in a vendor-neutral image database that is ready for use by whatever future PACS may be chosen; this normalization is what makes VNA-to-VNA migration and PACS replacement possible without data loss
What VNA does not do — VNA is primarily a storage and access layer; it does not provide intelligent data lifecycle management, automated tiering to lower-cost tiers, metadata enrichment for AI, or sensitive data governance; these capabilities require a data management layer above the VNA, which is where Komprise operates
How VNA Works with NAS
VNA and NAS have a close, complementary relationship that has been central to healthcare storage architecture for decades:
- VNA software runs on commodity servers and uses NAS as its underlying storage infrastructure; the VNA manages the DICOM database and access layer while NAS provides the physical storage capacity
- Storage infrastructures have been eliminated from PACS at the hardware and file system level and are supplied by non-domain-specific storage vendors; NetApp, Dell, IBM, and other NAS vendors provide the storage that VNA systems write to and read from
- Modern VNA architectures support tiered NAS storage — recent studies on high-performance NAS, older studies on lower-cost NAS tiers or cloud object storage — but most VNA systems require manual configuration of these tiers and do not automate lifecycle management intelligently
- Komprise fills this gap by analyzing VNA data at the NAS level and automating policy-driven tiering between NAS tiers and cloud object storage transparently, without requiring VNA-specific APIs or changes to VNA configuration
- Implementation of a VNA and enterprise imaging solution resulted in more than 10% cost savings, 30% reduction in storage costs, superior support for disaster recovery, and 80% decrease in unscheduled outages — despite a 120% increase in archive retrieval needs and 40% growth in image production; adding Komprise intelligent tiering on top of VNA compounds these savings further by automating the cold data lifecycle that VNA alone does not manage
Primary VNA Vendors
Vendor Neutral Archive (VNA) & PACS Market worth $8.57 billion by 2031 | MarketsandMarkets™.
The major vendors VNA vendors are:
- Fujifilm (TeraMedica Evercore) — Fujifilm understood early that data sovereignty matters more than the viewer; they prioritize the VNA and their strategy is content management across any file format from any department; market leader in enterprise VNA Dell EMC
- Philips (Clinical Repository) — strong integration with Philips PACS and cardiology; supports DICOM and non-DICOM content with metadata tagging for AI
- Hyland (formerly Acuo) — strong in multi-departmental enterprise imaging including cardiology, ophthalmology, and pathology alongside radiology
- Sectra — integrated VNA within enterprise imaging platform; high KLAS scores; strong in multi-site health systems
- GE HealthCare (Genesis Cloud Suite) — launched Genesis Cloud Suite in March 2025 as an enterprise imaging SaaS portfolio with VNA and data migration on AWS Gartner
- Intelerad (Ambra) — cloud-native VNA with strong multi-site and teleradiology integration
- IBM (Merge/Merge Healthcare) — deep integration with IBM Cloud; strong in North American academic medical centers
- Siemens Healthineers — VNA integrated with syngo enterprise imaging platform; strong in European markets and large academic health systems
NAS Vendors Commonly Used with PACS and VNA
The primary NAS vendors whose storage platforms sit beneath PACS and VNA systems in healthcare:
- NetApp — most widely deployed NAS in healthcare imaging; ONTAP integrates natively with Komprise for transparent tiering of DICOM data; AFF all-flash arrays for hot PACS storage, StorageGRID object storage for archival tiers
- Dell (PowerScale / Isilon) — widely deployed in large health systems for PACS storage; scale-out NAS architecture handles petabyte-scale DICOM archives; integrates with Komprise for cross-tier lifecycle management
- IBM Spectrum Scale — used in academic medical centers and research hospitals with large genomics and pathology data alongside DICOM imaging
- VAST Data — growing adoption in AI-forward health systems for high-performance imaging and AI inference workloads; Komprise is a VAST Cosmos partner
- Nasuni — cloud-native NAS increasingly adopted in health systems consolidating multi-site PACS storage to cloud; integrates with Komprise for intelligent tiering and lifecycle management
- AWS S3 / Azure Blob / Google Cloud Storage — cloud object storage destinations for cold DICOM archive tiers; all three integrate with Komprise Transparent Move Technology for transparent access from PACS without rehydration
What is a VNA and how does it differ from a PACS?
A VNA is a long-term, vendor-neutral image archive that stores DICOM files in open standard format independently of any PACS vendor. A PACS is the clinical workflow system that manages image acquisition, reading, reporting, and distribution for active studies. Today, cloud-native PACS separates the data layer, typically a VNA, from the application layer of viewers and workflow tools, enabling institutions to scale storage independently of their software contracts. The practical distinction is that PACS manages the active clinical imaging workflow and VNA manages long-term storage and portability. Many organizations run both, with VNA providing the storage foundation and PACS providing the clinical interface on top of it.
Does a VNA solve the storage cost problem for healthcare organizations facing the flash price surge?
A VNA solves the vendor lock-in problem and provides a more flexible storage foundation than proprietary PACS — but it does not automatically optimize costs. Without active lifecycle management, VNA archives accumulate cold studies on expensive storage tiers indefinitely. With flash and NAND prices projected to rise 130% by end of 2026, a VNA alone is not sufficient. Healthcare organizations need an intelligent data management layer above the VNA that actively identifies cold studies, tiers them to lower-cost object storage transparently, and compresses backup and DR footprints alongside hardware costs. Komprise Flash Stretch provides exactly this capability for VNA environments, reclaiming 70%+ of primary storage capacity without disrupting VNA access patterns or clinical workflows.
How does Komprise make VNA content AI-ready?
Komprise makes VNA content AI-ready through four integrated steps:
- The Global Metadatabase indexes VNA content including DICOM header attributes, study metadata, access patterns, and PHI status across the full archive without moving any data.
- KAPPA Data Services enrich that metadata with custom attributes extracted from DICOM headers at petabyte scale using serverless processing, making the VNA archive precisely queryable by clinical and research criteria.
- Komprise Deep Analytics queries the Global Metadatabase to find and tag exactly the right files for a given use case. That query then becomes the foundation for a Komprise Smart Data Workflow, which automates the actions taken on that curated dataset — including metadata enrichment via KAPPA, sensitive data exclusion, and delivery to any AI service.
- Intelligent AI Ingest delivers the curated dataset to any AI stack up to 2x faster than standard transfer tools, with full governance and audit trails. The result is VNA content that is governed, precisely curated, and delivered to AI pipelines efficiently — without the petabyte-scale data movement that would otherwise make healthcare AI initiatives cost-prohibitive.
What should healthcare IT teams look for when evaluating a data management solution for VNA environments?
Healthcare IT teams should evaluate VNA data management solutions against five criteria.
- Storage agnosticism — the solution must work across any VNA vendor (Philips, Sectra, Intelerad, Hyland, and others) without requiring vendor-specific integrations or replacements.
- Transparent access — cold studies tiered off primary VNA storage must remain accessible from their original location with no change to PACS or clinical application workflows.
- DICOM metadata fidelity — the solution must preserve all DICOM header attributes and access controls throughout every data movement operation.
- AI data preparation — the solution should provide cross-archive metadata indexing, enrichment, and curation capabilities that make VNA content directly usable for AI training and inferencing without secondary migration projects.
- PHI governance — built-in sensitive data detection and remediation must operate consistently across VNA, PACS, cloud, and NAS storage from a single governance framework, maintaining HIPAA compliance throughout every data lifecycle operation.