Komprise Intelligent Data Management Architecture Overview

Explosive data growth requires a re-think of how data is managed. Storage capacity is running out, backups are taking longer, and budgets can’t keep up with the unstructured data deluge. Managing data within vendor silos leads to poor visibility, proprietary lock-in, and ballooning costs. Komprise provides a standards-based, modern data management solution architected to put you in control of your data with unprecedented simplicity – by giving you visibility into all your data, moving data to the right place at the right time efficiently, and providing native access to data at every tier without proprietary lock-in.

Komprise Intelligent Data Management white paper highlights:

• Today’s Data Management Challenges
• The Principles of Komprise Technology
• The 7 Components of the Komprise Architecture
• How it Works

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Download this white paper to learn more about Komprise Intelligent Data Management

From dynamic data analytics, to Transparent Movement Technology (TMT), to direct data access, with Komprise Intelligent Data Management, you are able to know first, move smart, and take control of massive unstructured data growth while cutting 70% of enterprise storage, backup, and cloud costs.

Know First. Move Smart. Take Control of Unstructured Data Growth and Costs.

Your data will outlive your storage infrastructure. A storage-centric approach to data management misses the point. Read more.

What are the core architectural principles behind Komprise Intelligent Data Management and why do they matter at petabyte scale?

The Komprise architecture is built on three foundational principles that distinguish it from storage-vendor-native and agent-based data management approaches: know first, move smart, and take control. These principles are expressed in seven architectural components that work together to deliver data visibility, mobility, and AI value across any hybrid storage environment at petabyte scale. The core principles:

• Standards-based, agentless design — Komprise connects to any NAS, cloud, or object storage using standard NFS, SMB, and S3 protocols with no agents, no stubs, and no software installed on storage systems or endpoints; this eliminates the compatibility issues, upgrade dependencies, and performance overhead that agent-based approaches create
• Never in the hot data path — Komprise Observers operate out-of-band, analyzing and moving data without intercepting active user or application access; storage and application performance are completely unaffected during analysis, tiering, migration, metadata enrichment, and AI workflow operations
• Stateless, scale-out Observer grid — Komprise runs on a distributed grid of stateless virtual appliances with no central database and no single point of failure; the platform scales horizontally by adding Observers, with Komprise Elastic Shares technology applying dynamic partitioning to keep all compute resources fully utilized during large-scale processing jobs
• Data as a layer independent of storage — Komprise treats data management as a separate layer above storage hardware, enabling consistent policy enforcement, analytics, and AI data workflows across any combination of vendors and clouds without being constrained by any single vendor’s file system or product roadmap
• Proven at enterprise scale — the architecture is proven at 100PB+ across enterprise customers managing data across NetApp, Dell, IBM, VAST Data, Nasuni, Everpure, AWS, Azure, and Google Cloud simultaneously from a single platform

What are the components of the Komprise architecture and how do they work together?

The Komprise Intelligent Data Management architecture consists of seven integrated components that span data analysis, movement, access, governance, and AI enablement. The original architecture white paper describes these components, which have since been extended with newer capabilities including the Global Metadatabase, KAPPA data services, and Smart Data Workflows:

• Komprise Analysis — the analytics engine that continuously indexes all file and object data across every storage silo, building the Global Metadatabase with standard and enriched metadata including file age, type, owner, access patterns, sensitivity status, and custom tags; provides unified visibility and cost projection across the full hybrid estate
• Deep Analytics — policy-driven query engine that runs rich, cross-silo searches across the Global Metadatabase to identify precise datasets for tiering, migration, compliance, or AI use cases; the foundation for all Smart Data Workflows
• Transparent Move Technology (TMT) — patented file-level tiering that moves cold data to any lower-cost destination transparently, maintaining file-to-object duality so users and applications access files from their original location with no disruption and zero rehydration penalty
• Elastic Data Migration — high-performance, analytics-driven migration engine that moves file and object data up to 27x faster than standard tools with full metadata fidelity, integrity checks, and chain of custody reporting across any source and destination combination
• Smart Data Workflows — automated, policy-driven workflows that orchestrate discovery, classification, metadata enrichment, sensitive data governance, and AI data ingestion across the full unstructured data estate; directly invocable by agentic AI systems at runtime
• KAPPA Data Services — serverless processing layer that executes custom metadata extraction functions across petabyte-scale datasets using a few lines of Python; extracts domain-specific metadata from proprietary file formats including DICOM, genomics BAM, and financial documents, writing enriched attributes back to the Global Metadatabase
• Global Metadatabase — the unified, continuously updated index of all standard and enriched metadata across all storage silos; the central intelligence layer that powers Deep Analytics queries, Smart Data Workflows, AI data curation, and sensitive data governance across the entire hybrid estate

How does the Komprise architecture scale to 100PB+ without creating bottlenecks or single points of failure?

Scaling to 100PB+ requires an architecture that eliminates the central bottlenecks that make traditional data management platforms fail at enterprise scale. Komprise achieves this through four architectural decisions that compound each other:

• Stateless Observer grid — Komprise Observers are stateless virtual appliances that run independently with no coordination through a central server; each Observer processes the storage it is assigned to locally, and Observers can be added horizontally without reconfiguring the platform or migrating data
• No central database — unlike metadata-based architectures that route all queries through a central metadata server, Komprise distributes its Global Metadatabase across the Observer grid; there is no query bottleneck and no single point of failure that grows more vulnerable as data volumes increase
• Elastic Shares dynamic partitioning — Komprise Elastic Shares technology continuously redistributes processing tasks across the Observer grid in a streaming fashion as each Observer completes its work; machines never go idle mid-job, and the platform delivers near-linear speed-up regardless of how unevenly data is distributed across directory hierarchies
• Local processing at the data source — Observers process data locally adjacent to the storage they analyze, minimizing WAN traffic and latency; Komprise Hypertransfer then moves data 25x faster over WANs when data movement is required, and Intelligent AI Ingest delivers curated datasets to AI services 2x faster than standard transfer tools
• Proven scale — the architecture is deployed and proven at 100PB+ in production enterprise environments, with no architectural changes required to scale from hundreds of terabytes to exabyte-class deployments

How does the Komprise architecture enable AI data workflows and what makes it better suited for AI than storage-vendor-native approaches?

The Komprise architecture was designed to manage data as a layer independent of storage, which makes it uniquely well-suited for AI data workflows that must span multiple storage silos, vendors, and cloud environments. Storage-vendor-native tools can only manage data within their own ecosystem; Komprise manages all of it from one platform. The architectural advantages for AI:

• Cross-silo Global Metadatabase — Komprise continuously indexes all unstructured data across every NAS, cloud, and object storage environment into a single, queryable Global Metadatabase; this unified metadata layer is what enables Smart Data Workflows to find exactly the right files for any AI use case across a petabyte-scale, heterogeneous data estate
• KAPPA serverless processing — the stateless Observer grid that powers Komprise’s scale also underpins KAPPA Data Services; KAPPA functions execute as serverless workloads distributed across the grid, applying custom metadata extraction at petabyte scale without provisioning or managing dedicated infrastructure
• AI pipeline automation — Smart Data Workflows automate the full AI data preparation sequence: cross-silo discovery via the Global Metadatabase, noise filtering, sensitive data exclusion, metadata enrichment via KAPPA, and governed ingestion to any AI service; agentic AI systems can directly invoke KAPPA functions and Smart Data Workflows at runtime for just-in-time data preparation
• Zero-move intelligence — the Komprise architecture indexes and enriches metadata in place without moving files; AI pipelines receive precise, governed dataset definitions and fetch only the specific files they need, only when they need them, rather than copying petabytes of data upfront
• No hot data path interference — because Komprise Observers operate out-of-band, AI workflow automation and metadata enrichment jobs never impact the performance of the storage systems or applications that depend on the same data

How does the Komprise architecture support enterprise security, compliance, and governance requirements across hybrid storage environments?

Enterprise security and compliance requirements demand that data governance be consistent, auditable, and enforced across every storage environment — not just within a single vendor’s platform. The Komprise architecture delivers this through a combination of design principles and dedicated capabilities:

• Local data processing — Komprise processes all data locally within the customer’s own data center or cloud environment; no file content is ever sent to Komprise infrastructure, and sensitive data stays in place; this is particularly important for healthcare, financial services, and public sector organizations with strict data residency and sovereignty requirements
• Agentless deployment — no software agents are installed on storage systems, endpoints, or application servers; deployment requires only virtual appliance provisioning and standard protocol connectivity, and is measured in hours rather than months with no changes to existing storage or application configurations
• Sensitive data detection and remediation — Komprise Sensitive Data Management uses built-in PII and PHI scanners, custom regex, and integrations with third-party AI content scanners to detect sensitive data across the full estate; files are automatically tagged in the Global Metadatabase and can be confined, moved, or excluded from AI workflows by policy, with no modification to the original file
• Full audit trails — every analysis, data movement, metadata enrichment, and AI workflow operation is logged with complete lineage showing what data was touched, by which workflow, when, and by which policy; these audit records support HIPAA, GDPR, and internal governance reporting requirements
• Ransomware defense by architecture — because Komprise moves cold files off primary storage to immutable object destinations using file-level tiering, the ransomware attack surface shrinks as a direct byproduct of cost optimization; tiered files stored with object lock retention are protected even if primary storage is compromised, with clean recovery from prior versions available without paying ransom