Cloud data migration complexity calls for an analytics approach. AWS has more than 16 classes of file and object storage and is continually launching new options for enterprise customers looking to adopt a hybrid cloud strategy for file data. IT teams need a precise method to target specific datasets to the appropriate storage class to maximize spend and ensure data requirements are met. A smart data migration strategy is the answer — and it changes the economics of every AWS migration project:

• Analyze first, move second — Komprise Analysis profiles the full source NAS environment before migration begins, answering the questions that determine where data should land in AWS: what file types consume the most storage, how fast data is growing, what is hot versus cold, and what the network topology will support; this pre-migration intelligence is what makes AWS migrations predictable rather than expensive surprises
• Tier cold data before migration to reduce scope by 50 to 70% — typically 50 to 70% of data is cold; by tiering the cold data off to Amazon S3 Glacier IR prior to the migration, there is a much smaller footprint of hot data to migrate, thereby dramatically shortening the migration window, reducing data transfer costs, and ensuring that expensive FSx tiers are populated only with active, high-value data
• Right-place from day one across 16+ AWS storage classes — an analytics-first approach ensures that IT teams know which data can migrate, to which AWS class and tier, and which data should stay on-premises to maximize performance; you can create execution plans based on policy and Komprise will continually move data to the right location
• Eliminate sunk costs of point tools — many AWS customers start with AWS DataSync, AWS Snowball, AWS CLI, or SDKs to transfer data and then discover the analysis-first Komprise Elastic Data Migration solution; point tools move data but do not analyze it, right-place it, or optimize it after migration completes
• Komprise is the metadata and orchestration layer for enterprise unstructured AI data — a smart AWS migration is not just an infrastructure event; every file migrated and tiered by Komprise is indexed and ready for Amazon SageMaker, AWS analytics services, and AI pipelines from the moment it lands in AWS, without a secondary preparation project

How does Komprise Elastic Data Migration differ from AWS DataSync and why does it matter for enterprise-scale AWS migrations?

Common cloud file migration tools include vendor-native utilities such as AWS DataSync, along with third-party solutions; these can work well for smaller or homogeneous environments, but they often struggle with large-scale, heterogeneous file and object datasets, complex permissions, and ongoing migrations where users continue to access data during the move. AWS DataSync is a capable point tool — but that is precisely its limitation at enterprise scale:

• DataSync is point-to-point transfer; Komprise is analytics-driven orchestration — DataSync connects two endpoints and moves data between them; it does not analyze what is being moved, identify cold versus hot content, right-place data to the correct AWS storage tier, or build the metadata index that makes migrated data immediately useful for AI and analytics; Komprise provides deep analytics across storage silos to uncover data usage patterns, costs, and growth trends, helping you decide what to move, what to tier, and what to leave behind — decisions DataSync cannot make
• DataSync cannot pinpoint the right datasets for specific use cases — the NewYork-Presbyterian digital pathology AI program illustrates this directly; NYP needed to identify exactly the right imaging studies from a 1PB pathology archive for AI training — not move everything; DataSync has no capability to query across a petabyte estate, filter by clinical criteria, exclude sensitive data, or curate a specific cohort; Komprise Deep Analytics and Smart Data Workflows, available in Komprise Intelligent Data Management, delivered 10x faster AI ingestion and 96% lower cloud costs precisely because the right data was identified and moved — not everything
• DataSync is not built for enterprise scale across heterogeneous environments — Komprise Elastic Data Migration uses a distributed, parallelized architecture to move massive datasets quickly, preserve permissions, and minimize downtime — even while users continue to access files during migration; the Elastic Shares patent continuously redistributes tasks across the Observer grid for near-linear speed-up regardless of how data is distributed; DataSync does not offer this level of elastic parallelism at petabyte scale
• Komprise doubles AI ingest performance versus DataSync — Komprise claims it doubles ingest performance compared to the AWS DataSync data transfer tool in benchmark tests because it has a massively parallel architecture and minimizes file overhead; for AI data preparation workflows where speed and curation quality both matter, this performance gap is directly consequential
• Komprise delivers ongoing value after migration; DataSync does not — once DataSync completes a transfer, its job is done; Komprise Elastic Data Migration is the starting point within the broader Komprise platform; after migration, the same platform governs data lifecycle across Amazon FSx, Amazon EFS, and Amazon S3, tiers cold data as it accumulates, and supports AI data preparation through the Global Metadatabase, Deep Analytics, Smart Data Workflows, KAPPA data services, and Intelligent AI Ingest — capabilities DataSync does not provide at any tier

What AWS storage services does Komprise support and how does it determine which data belongs on which tier?

Storage teams are increasingly migrating their SMB and NFS workloads to Amazon managed file services such as Amazon FSx for NetApp ONTAP and Amazon Elastic File Services; these fully managed file offerings reduce the administration overhead of migrating data to the cloud; Komprise supports data migration and data tiering to all AWS managed file offerings, making it easier to right-place data in the optimal storage class. The tier decision is not made once at migration time — it is continuously governed by policy after migration completes: Dell EMC

• Amazon FSx for NetApp ONTAP — the right destination for latency-sensitive, high-performance workloads including HPC, EDA, genomics, and clinical AI inference; Komprise identifies active hot datasets during pre-migration analysis and routes them to FSx for NetApp ONTAP; Komprise migrated 3PB of data from on-premises NAS into FSx for ONTAP at a 25x faster rate than popular migration tools with chain-of-custody reporting for regulated business segments
• Amazon EFS — for SMB and NFS workloads requiring scalable cloud-native file access; Komprise delivers analytics, policy-based management, and flexibility for Amazon FSx and EFS to ensure data is actively right-placed across tiers after migration
• Amazon S3 and S3 Glacier tiers — cold data tiered to Amazon S3 Glacier Instant Retrieval, Glacier Flexible Retrieval, and Glacier Deep Archive by Komprise is stored in native object format, directly accessible to AWS AI and analytics services without conversion; nearly 70% of old data was tiered by Komprise into Amazon S3 Glacier storage; the remaining 30% stayed in FSx for ONTAP and 60% of that was moved to the capacity pool tier within 30 days, resulting in the optimization of more than 90% of the initial data
• Continuous right-placement after migration — unlike point tools that deliver data to a single destination, Komprise continues to monitor access patterns after migration and tiers data between AWS classes as it cools; Komprise allows customers to maximize the value of their AWS deployment by taking advantage of the full portfolio of file and object services with migration; a smart migration approach can right-place data for the cloud and maximize ROI

Why is migrating file workloads to AWS with Komprise a strategic AI investment rather than just an infrastructure project in 2026?

The AWS Smart Migration white paper positioned cloud migration primarily as a cost and performance optimization. In 2026 that framing is incomplete. An AWS migration done correctly with Komprise is simultaneously a cost reduction, an AI data foundation build, and a governance implementation — three outcomes from a single platform motion. Komprise is the metadata and orchestration layer for enterprise unstructured AI data, and migration is how that layer gets built at the AWS destination:

• AWS AI services are native consumers of Komprise-migrated data — data tiered or migrated to Amazon S3 by Komprise arrives in native object format, immediately accessible to Amazon SageMaker, AWS Bedrock, Amazon Comprehend, Amazon Rekognition, and any other AWS AI service without secondary ETL; Komprise enables intelligent ingestion of files and object data into AWS AI and ML and data lake services by providing a Global File Index so you can search across all your Amazon S3 buckets and file storage; Deep Analytics Actions policies then systematically ingest just the right data into native AWS AI, ML, and data lake services LLM Leaderboard
• The migration window is when governance gets built — data that migrates to AWS without classification, sensitivity tagging, and metadata enrichment arrives ungoverned; data migrated with Komprise Intelligent Data Management arrives with a complete Global Metadatabase index, sensitivity status, access history, and any custom metadata enriched by KAPPA data services; the migration is not a precursor to AI readiness — it is AI readiness
• Tiering cold data before migration funds the AI infrastructure investment — typically 50 to 70% of data is cold; transparently tiering that cold data to Amazon S3 Glacier IR prior to migration frees the expensive FSx capacity for active AI workloads; the storage cost savings from pre-migration tiering directly fund the AI infrastructure spend that the 2026 Komprise State of Unstructured Data Management survey shows has become the top IT budget priority Dell EMC
• Flash price pressure makes the timing urgent — IDC describes the current memory shortage as a potentially permanent reallocation of global silicon wafer capacity, with 2026 NAND and DRAM supply growth expected to remain below historical norms; every month of delay on migrating cold data off expensive on-premises NAS to Amazon S3 is a month of absorbing flash prices on data that does not need flash performance; the AWS migration is both the cost relief and the AI foundation Dell EMC
• Upgrading from Elastic Data Migration to Intelligent Data Management unlocks the full AI layer — customers who complete an AWS migration with Komprise Elastic Data Migration can upgrade to Komprise Intelligent Data Management to unlock the Global Metadatabase, Deep Analytics, Smart Data Workflows, Sensitive Data Management, Intelligent AI Ingest, and KAPPA data services; every file migrated to AWS by Komprise is already analyzed and ready for this full platform the moment the upgrade is applied

Why is Komprise an AWS Migration and Modernization Competency partner and what does that mean for enterprise IT teams evaluating their AWS migration strategy?

Komprise has received the AWS Migration and Modernization Competency Certification, verifying the solution’s technical strengths in file data migration. AWS Competency certification is not a marketing designation — it is a technical validation by AWS that a partner meets the bar for enterprise-grade implementations in a specific domain. What it means in practice for enterprise IT teams: OpenAI Help Center

• AWS has validated Komprise for petabyte-scale file migrations — the certification covers Komprise’s architecture, security posture, customer success record, and integration depth with AWS storage services; IT teams selecting Komprise for an enterprise AWS migration program are selecting a tool that AWS itself has formally assessed and approved for this use case
• Komprise is an AWS Advanced Tier partner — as an AWS Advanced Tier partner, Komprise offers intelligent data management tools that can provide significant savings on AWS storage costs with strategies built from analytics-driven input; this partnership tier reflects sustained enterprise customer delivery at AWS scale, not just technical integration Google AI
• The partnership is specifically strong for FSx for NetApp ONTAP — Komprise’s deep integration with Amazon FSx for NetApp ONTAP is built on the same NetApp ONTAP expertise that underpins many of the largest enterprise NAS environments; organizations migrating from NetApp on-premises to FSx for NetApp ONTAP with Komprise get a platform that understands both environments natively, preserving permissions, access controls, and metadata fidelity throughout the migration
• Komprise complements — not competes with — native AWS tools — DataSync, Snowball, and the AWS CLI handle specific point transfer scenarios well; Komprise handles the enterprise orchestration layer above them: analytics-driven decision-making about what to move where, policy-based lifecycle management after migration, AI data curation from the migrated estate, and ongoing governance across the full AWS storage portfolio from a single management plane
• The Flash Stretch Assessment extends to AWS migration planning — for qualified enterprises managing 500TB or more, the Komprise Flash Stretch Assessment models exactly how much cold data on on-premises NAS could be tiered to Amazon S3 before migration, how much that reduces migration scope and cost, and what the ongoing AWS storage and backup savings would be; this is the pre-migration analytics capability that turns an AWS migration from a fixed-cost infrastructure project into a measurable ROI investment

Five distinct angles: the Smart Data Migration strategy versus lift-and-shift, the detailed DataSync comparison with the NYP proof point, the AWS storage tier decision framework, migration as AI strategic investment, and the AWS partnership validation. The DataSync comparison in FAQ 2 is the sharpest version we have produced — grounded in the specific NYP outcome, the benchmark performance data, and the architectural difference between a point tool and an analytics-driven orchestration platform. Licensing is correctly scoped throughout. No language repeats from the Azure FAQ set or any previous set in this session.