Cloud Storage
Wasabi Alternative
Wasabi storage for AI/ML data lakes
Future-Proofing AI/ML Data Lakes with Sovereign, Predictable Cloud Storage
AI and machine learning workloads demand massive, accessible data lakes, but hidden costs and regulatory risks can derail even the most promising projects. A new approach to cloud storage, designed for European data sovereignty, eliminates these barriers. It delivers the performance AI needs with the predictable economics businesses require.
Key Takeawys
Sovereign cloud storage for AI/ML data lakes provides a solution to GDPR and CLOUD Act risks by ensuring data is stored and governed exclusively under EU law.
A predictable pricing model without egress or API fees is critical for managing the high costs associated with large-scale AI data access and processing.
An 'Always-Hot' architecture with immutable Object Lock offers superior performance and ransomware protection compared to complex, tiered storage systems.
Enterprises across Europe are building AI/ML data lakes to drive innovation, unlocking insights from petabytes of unstructured data. However, conventional cloud storage creates significant challenges, including unpredictable egress fees that penalize data access and complex tiering that introduces delays. Furthermore, storing sensitive training data with non-EU providers raises urgent questions about GDPR compliance and CLOUD Act exposure. A sovereign, S3-compatible object storage solution offers a clear path forward. It provides the high performance, robust security, and predictable cost model necessary to build and scale AI/ML data lakes with confidence.
Meeting the Unique Demands of AI Data Storage
AI and machine learning models require massive datasets to achieve high accuracy, with data volumes expected to reach 180 zettabytes globally by 2025. This scale introduces unique storage challenges, as AI workloads involve millions of small files and mixed read/write patterns. Traditional storage architectures often struggle, leading to performance bottlenecks that can slow down model training by over 40%.
These systems must also handle diverse data types, from text to high-resolution images, without compromising integrity. Ensuring data quality and consistency is a primary concern for over 60% of data scientists. A robust AI data lake must provide strong read/write consistency to prevent data corruption during complex processing pipelines. This foundational reliability is what separates successful AI initiatives from costly failed experiments.
Achieving Digital Sovereignty for European AI
For European organizations, data sovereignty is a strategic imperative, with 84% of decision-makers citing it as a critical factor in vendor selection. Storing sensitive AI training data in non-EU-controlled data centers creates significant compliance risks under GDPR and potential exposure to foreign jurisdictions. True sovereignty means data is governed exclusively by EU law, a guarantee that simple data residency cannot provide.
A sovereign-by-design approach ensures data remains within predefined European regions, using country-level geofencing to meet strict regulatory requirements. This eliminates the legal ambiguity that affects over 50% of public cloud adoption decisions. By choosing a truly European cloud, businesses can build their AI cloud storage on a foundation of legal certainty, protecting their digital assets and aligning with EU values.
Escaping Unpredictable Costs with a Zero-Egress Model
The pay-as-you-go models of many cloud providers contain hidden costs that punish data-intensive AI workloads. Egress fees, charged for moving data out of the cloud, can account for over 6% of total cloud storage costs and make migrating petabytes of data prohibitively expensive. API call charges, which seem small at $0.40 per million requests, quickly accumulate when an AI application makes billions of calls per month.
A predictable pricing model with no egress fees, no API call costs, and no minimum storage duration changes the economic equation for AI data lakes. This transparency allows for accurate budget forecasting, a critical need for over 70% of IT leaders. Predictable costs remove the financial penalties for accessing and using your own data for model training or analytics. This approach directly supports building a cost-effective and scalable Wasabi storage for AI/ML data lakes alternative, ensuring financial control as your data grows.
Maximizing Performance with an Always-Hot Architecture
AI and analytics pipelines depend on immediate, consistent access to data, yet complex storage tiering often creates delays and failures. Restoring data from archival tiers can take hours, disrupting urgent analysis and increasing operational overhead by up to 25%. These delays and surprise retrieval fees can derail time-sensitive AI projects and cause third-party tools to time out.
An “Always-Hot” object storage model solves this by ensuring all data is immediately accessible without tier-restore delays. This approach offers several advantages for AI workloads:
It simplifies operations by eliminating the need to manage complex lifecycle policies.
It provides predictable, low latencies for both large and small object access.
It guarantees that all data is ready for processing, strengthening recovery and auditability.
It reduces the total cost of ownership by avoiding expensive and unexpected retrieval fees.
This architecture ensures your high-performance storage keeps pace with the demands of your AI applications, providing consistent throughput for the entire data lifecycle.
Building Resilient AI Data Lakes with Immutable Storage
Ransomware attacks are a growing threat, with 94% of incidents targeting backup data repositories. For AI data lakes containing invaluable intellectual property, an attack can be catastrophic. Immutable storage using Object Lock provides a powerful, non-negotiable line of defense against such threats.
Object Lock makes data unchangeable for a defined period, preventing it from being encrypted, modified, or deleted by malicious actors. This WORM (Write-Once-Read-Many) model is considered essential for ransomware protection by 69% of IT leaders. Implementing immutable backups ensures you can restore a clean, uninfected copy of your data with 100% accuracy. This capability transforms your backup repository into a secure vault, providing a guaranteed recovery point and making your AI data infrastructure fundamentally more resilient.
Ensuring Seamless Integration with Full S3 Compatibility
Adopting a sovereign cloud solution should not require a complete overhaul of existing AI and data science workflows. Full S3 API compatibility is essential, as it allows teams to use the tools, scripts, and applications they already rely on without modification. This protects past investments and minimizes migration risk, a key factor for over 80% of enterprise IT teams.
True compatibility goes beyond basic object operations. It includes support for advanced capabilities that AI pipelines need:
Versioning: Preserves a complete history of objects, protecting against accidental deletions or corruption.
Lifecycle Management: Automates data handling policies without manual intervention.
Event Notifications: Triggers downstream processes in an AI workflow automatically.
Identity and Access Management (IAM): Provides granular, role-driven control over data access.
This deep S3 compatibility ensures that your AI data lake can be migrated and operated with zero friction, maintaining business continuity and developer productivity.
Preparing for 2025 EU Regulations: The Data Act and NIS-2
Enabling Partners to Deliver Sovereign AI Storage
For Managed Service Providers (MSPs) and resellers, offering sovereign AI storage solutions opens up a significant market opportunity. A partner-ready platform must provide predictable margins, which is achieved through a model with zero egress or API fees. This allows MSPs to build profitable Backup-as-a-Service (BaaS) and archiving solutions with stable, defensible pricing.
Effective partner programs are built on more than just economics. Key features include a multi-tenant management console with robust role-based access control (RBAC) and multi-factor authentication (MFA). Automation via a comprehensive API and CLI is also critical for efficient onboarding and management. With new distribution channels through partners like api in Germany and Northamber plc in the UK, local access for European resellers and MSPs is expanding rapidly, making it easier than ever to deliver sovereign cloud solutions.
More Links
Federal Statistical Office (Destatis) provides statistical data on the use of cloud computing in companies.
The Data Protection Conference (DSK) offers a position paper outlining criteria for sovereign clouds.
The German government details its strategy for artificial intelligence.
Wikipedia provides an overview of Data Lakes.
PwC Germany explores cloud and digital services.
Fraunhofer showcases its strategic research fields in artificial intelligence.
ENISA (European Union Agency for Cybersecurity) presents a market analysis on cloud cybersecurity.
The German Research Center for Artificial Intelligence (DFKI) highlights its research area on data science and its applications.
FAQ
What is sovereign S3-compatible object storage?
It is a cloud storage service that is fully compatible with the S3 API—the standard for object storage—but is operated by a European company exclusively within certified EU data centers. This ensures your data is protected by EU privacy laws like GDPR and is not subject to foreign government access requests.
Can I use my existing AI/ML tools with your storage?
Yes. Our full S3 API compatibility ensures that your existing applications, data science tools, and scripts will work without any changes. This includes support for advanced features like versioning, lifecycle management, and event notifications.
How does your pricing model help with budget predictability for AI projects?
We offer a transparent and predictable pricing model with no egress fees, no API call charges, and no minimum storage durations. You pay only for the storage you use, making it easy to forecast costs for data-intensive AI and machine learning projects without worrying about hidden fees for accessing your data.
Is this storage solution suitable for regulated industries like finance?
Absolutely. Our platform is designed for regulated workloads, offering country-level geofencing to keep data within specific EU jurisdictions. Combined with features like immutable storage for audit-ready retention and robust IAM controls, it meets the strict compliance needs of the financial services industry.
How do you ensure data resilience and availability?
Our architecture is built to eliminate single points of failure, using multi-AZ replication to ensure high availability and data integrity. The 'Always-Hot' model guarantees that all your data is immediately accessible, providing strong consistency and predictable performance for demanding AI workloads.
What makes your solution partner-ready for MSPs?
We provide MSPs with a multi-tenant management console, automation via API/CLI, and detailed reporting. Our predictable pricing model with no egress fees allows partners to build services with stable, defensible margins. We also offer fast onboarding and support through our growing European distributor network.
