Independent Vendor Intelligence
Unified Data Protection Across AWS, Azure, GCP, and Hybrid Cloud Environments
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Your cloud data protection platform platform reaches decision-makers actively evaluating solutions.
Get Featured →Comprehensive comparison framework with evaluation criteria, vendor scoring methodology, and procurement checklist.
Answer these questions to identify which platform approach suits your organisation.
1. What is your primary driver?
Data security → Veeam Data Platform | Operational simplicity → Druva Data Resiliency Cloud
2. What is your deployment preference?
Maximum control → Self-managed | Minimum overhead → Fully managed SaaS
3. What is your data environment?
Multi-cloud + on-prem → Hybrid platform | Cloud-only → Cloud-native platform
Nearly half of enterprise cloud data has no backup coverage. The shared responsibility gap between cloud providers and customers leaves an enormous risk exposure that most organisations underestimate.
82% of enterprises operate multi-cloud. Separate backup tools per cloud provider create complexity, inconsistency, and compliance gaps. Unified platforms provide consistent protection across all environments.
Ransomware attacks now target cloud infrastructure through compromised credentials, sync client propagation, and API abuse. Independent backup stored outside the production cloud account is the primary recovery mechanism.
Most organisations running Kubernetes have no application-level data protection. Native Kubernetes backup that understands pods, deployments, and persistent volumes is essential for containerised application recovery.
In-depth analysis for buyers evaluating cloud data protection platforms.
Cloud providers protect infrastructure — physical security, hardware redundancy, network availability. They do not protect your data against accidental deletion, malicious destruction, ransomware, policy misconfiguration, or application-level corruption. AWS, Azure, and GCP all operate shared responsibility models that explicitly place data protection responsibility on the customer. Yet 45% of cloud data remains unprotected by any backup solution, representing an enormous risk exposure that most organisations do not fully understand.
The gap is widened by cloud-native services that are particularly difficult to protect. Serverless functions, managed databases, containerised workloads, and object storage buckets each require different protection approaches. Native cloud snapshots provide some recovery capability but have significant limitations: they exist within the same cloud account (vulnerable to account compromise), retention is often limited, and cross-cloud recovery is not supported. Enterprise cloud data protection platforms close these gaps with independent, immutable copies stored outside the blast radius of a cloud account compromise.
With 82% of enterprises operating across multiple cloud providers, data protection cannot be siloed by cloud. Managing separate backup tools for AWS, Azure, and GCP creates operational complexity, inconsistent policy enforcement, and visibility gaps that make compliance reporting impossible. Unified multi-cloud data protection provides a single management plane for backup policies, recovery operations, and compliance reporting across all cloud environments.
When evaluating multi-cloud data protection, assess the depth of native integration with each cloud provider's services. Surface-level coverage that protects VMs but misses managed databases, serverless functions, and cloud-native storage fails to protect the workloads that organisations are increasingly adopting. True multi-cloud protection means native support for each provider's unique services — RDS, Aurora, DynamoDB on AWS; Azure SQL, Cosmos DB on Azure; Cloud SQL, BigQuery on GCP — not just VM backup replicated across clouds.
Buyer's Note: When evaluating cloud data protection platforms, request a proof-of-concept deployment against your actual environment. Vendor demonstrations using sanitised demo data do not reveal how the platform performs with your specific infrastructure, data volumes, and compliance requirements.
Two architectural approaches compete in cloud data protection. Cloud-native platforms (Druva, Clumio) are built from the ground up for cloud environments, operating as fully managed SaaS services that integrate via cloud APIs. Traditional platforms extended to cloud (Veeam, Commvault) add cloud protection capabilities to architectures originally designed for on-premises environments, providing broader hybrid coverage but potentially more management complexity.
For cloud-only organisations with minimal on-premises infrastructure, cloud-native platforms provide the simplest operational model — no backup servers to manage, no storage to provision, no software to update. For hybrid organisations with significant on-premises workloads alongside cloud, traditional platforms extended to cloud provide unified protection across both environments without requiring separate tools. The choice depends on your infrastructure reality, not vendor marketing. Honestly assess the ratio of cloud to on-premises workloads before selecting your architectural approach.
Cloud data protection platforms increasingly include disaster recovery capabilities — enabling organisations to failover workloads to cloud infrastructure during a disaster without maintaining dedicated DR sites. Disaster Recovery as a Service (DRaaS) leverages cloud elasticity to provision recovery infrastructure on demand, paying only during actual disaster events rather than maintaining idle DR infrastructure continuously.
The economics of cloud-based DR are compelling: replacing a physical DR site costing £500,000-2M annually with DRaaS at £50,000-200,000 reduces costs by 80-90% while potentially improving recovery capabilities. When evaluating DRaaS, test actual failover and failback procedures — the ability to fail over workloads is only valuable if failback to production is equally reliable. Also assess network configuration requirements, as maintaining network connectivity during failover to a cloud DR environment requires careful planning.
GenAI Warning: Organisations deploying GenAI are generating and processing unprecedented data volumes. Ensure your data protection platform can scale to protect AI training data, model artifacts, and the sensitive data that GenAI workloads ingest.
Kubernetes has become the default deployment platform for cloud-native applications, yet Kubernetes data protection remains a significant gap for most organisations. Kubernetes treats storage as ephemeral by default — persistent volumes must be explicitly protected. Traditional backup tools that operate at the VM or storage level do not understand Kubernetes constructs like pods, deployments, stateful sets, and persistent volume claims.
Cloud data protection platforms are adding Kubernetes-native protection that understands Kubernetes resource definitions, captures application-consistent snapshots including both persistent data and Kubernetes metadata, and enables granular recovery of individual applications within a cluster. When evaluating Kubernetes data protection, verify that the platform protects the complete application definition — not just the persistent volume but the full set of Kubernetes resources required to restore a running application.
Cloud data protection costs are driven by three factors: data storage (retained backup copies), data transfer (moving data between clouds or regions), and compute (processing backup and recovery operations). Without optimisation, cloud backup costs can escalate rapidly — particularly for organisations retaining long-term backup data that compounds monthly. Effective cost management requires deduplication to reduce storage footprint, intelligent tiering to move aged backup data to cheaper storage classes, and transfer optimisation to minimise cross-region data movement.
The most impactful cost control is deduplication — platforms achieving 60-70% deduplication ratios reduce storage costs proportionally across the entire retention period. Global deduplication (deduplicating across all backup sources, not just within individual backups) provides the highest ratios for organisations with multiple environments containing similar data. When comparing platform costs, request TCO projections at your actual data volumes and retention requirements rather than relying on vendor pricing calculators that may use optimistic assumptions.
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