How do I do EFS on Other Clouds?

The Search for the Right Network File System

In 2016, AWS Elastic File System (EFS) became generally available, introducing the first fully managed, elastically scalable NFS file storage service in the cloud. EFS eliminated the need for capacity planning and manual provisioning since storage scaled automatically based on usage, and users paid only for what they consumed. This represented a significant shift from traditional approaches that required either pre-provisioning fixed-capacity cloud volumes or managing physical storage infrastructure.

Following EFS's success, other major cloud providers launched competing managed NFS solutions. Google introduced GCP Filestore in 2017, Azure added NFS protocol support to Azure Files in 2020, and specialized high-performance options like AWS FSx for Lustre and Azure Managed Lustre emerged to address HPC and data-intensive workloads. These developments established fully managed, elastically scalable file storage as a standard offering across the major cloud platforms.

Core Features

Fully managed file stores serve diverse workloads: lift-and-shift migrations moving on-premises applications to the cloud, big data and analytics pipelines requiring shared access to datasets, content management systems serving media files, containerized applications needing persistent shared storage, and machine learning workflows processing large training datasets. While cloud providers offer competing solutions, they vary significantly in performance characteristics, pricing models, protocol support, and integration depth within their respective ecosystems.

For a service to truly match AWS EFS's capabilities, it must deliver four core features:

• Fully managed NFS service – eliminates server provisioning, patching, and maintenance overhead
• Automatic elastic scaling – storage capacity adjusts dynamically without manual intervention or downtime
• Concurrent multi-instance access – supports thousands of simultaneous connections from compute instances
• High availability and durability – data replicated across multiple availability zones with built-in redundancy
• Intelligent lifecycle management – automated tiering between performance and cost-optimized storage classes

This guide examines the leading alternatives to AWS EFS, comparing how each solution addresses these requirements. We'll evaluate options across major cloud platforms (Google Cloud, Azure, Oracle Cloud), analyze their performance profiles and pricing structures, and identify which scenarios favor each alternative. Whether you're planning a cloud migration, building a multi-cloud architecture, or optimizing costs for existing workloads, understanding these trade-offs will help you select the right file storage solution.

Other Cloud Providers

All major cloud providers now offer managed file storage services that support concurrent access from multiple servers. Below is a feature comparison of AWS EFS alternatives across different cloud platforms.

We've also included Archil, a cloud-agnostic solution that works across any provider with S3-compatible object storage. Unlike traditional file systems, Archil operates as a cache layer over object storage, offering a unique hybrid approach to file storage.

While there is a lot of feature overlap between the different cloud service providers there are a lot of key differences:

• Auto Scaling: AWS EFS and Archil automatically grow and shrink without pre-provisioning, while Azure Files and GCP Filestore require manual capacity allocation upfront.
• Protocol Support: Azure Files uniquely supports both SMB (Windows-native) and NFS, making it versatile for mixed environments.
• Storage Architecture: Archil differs fundamentally as a caching layer over object storage rather than a native file system, which affects performance patterns and use case suitability.
• Storage Tiers: AWS EFS offers the most granular lifecycle management with automatic tiering to Infrequent Access storage, while Oracle and Archil currently offer single-tier options.

AWS EFS and Oracle File Storage Service eliminate the need to forecast capacity, provision additional storage, or monitor utilization thresholds. Storage automatically expands and contracts with your actual usage, and you pay only for what you consume

For multi-cloud or hybrid environments, Azure Files offers distinct advantages with its dual SMB/NFS protocol support, enabling seamless integration across Windows and Linux systems. This makes it particularly valuable for organizations running mixed workloads or migrating gradually from on-premises infrastructure. However, this flexibility comes with trade-offs: Azure Files requires manual capacity planning and provisioning, meaning you'll need to monitor usage and adjust allocations as your needs change.

If you're operating across multiple cloud providers or want to avoid vendor lock-in, Archil provides a cloud-agnostic alternative that works with any S3-compatible object storage. Its caching architecture can reduce storage costs significantly while maintaining NFS compatibility, though performance characteristics differ from native file systems.

GCP Filestore suits workloads requiring predictable, high-performance file storage with strong integration into the Google Cloud ecosystem, particularly for Kubernetes-based applications on GKE, though it also requires upfront capacity provisioning.

Performance and Cost Considerations

When choosing between file storage solutions, understanding both performance characteristics and pricing models is essential. Performance capabilities vary across providers, and costs scale differently based on your usage patterns, making the "best" choice highly dependent on your specific workload requirements.

Performance Metrics

Each service offers different performance characteristics optimized for specific workload types. The table below compares key metrics, but remember: these represent theoretical maximums that require specific conditions to achieve.

** Performance metrics depend on total storage size, file system configuration, network conditions, and workload patterns. Actual performance varies significantly based on implementation.*

Across the different providers there is a wide variety in performance, however this varies even more based on your use case. For example, you can only reach max throughput if a large majority of your storage is allocated in the highest storage tiers. In some providers this will only occur if you are constantly near capacity for storage which can mean close to 64 TBs of data, far more than most use cases need.

When looking at the theoretical performance limits of the services, make sure you take into account your access pattern and workloads.

Cost Considerations

Pricing structures vary significantly across providers, with fundamentally different models for storage capacity, throughput, and data access. Understanding these differences is essential for accurate budgeting and cost optimization.

Pay-per-use vs. Provisioned Capacity:

• AWS EFS, Oracle, and Archil charge only for actual storage consumed, making them cost-effective for variable workloads or development environments where capacity needs fluctuate.
• Azure Files and GCP Filestore require provisioned capacity with minimum commitments (Azure Premium: 100 GB minimum; GCP Basic: 1 TB minimum). You pay for provisioned space regardless of actual usage, which can result in significant waste if you over-provision for peak capacity.

When evaluating costs, consider not just storage pricing but also your anticipated throughput needs, access patterns, and data transfer requirements. It's also important to account for latencies and costs when using storage and compute across different cloud providers so it is a good idea to keep your storage and compute together.

Choosing the Right Solution

Each major cloud provider has built capable file storage solutions optimized for their own ecosystems. AWS EFS excels within AWS, Azure Files integrates seamlessly with Microsoft services, and GCP Filestore pairs naturally with Google Cloud workloads. These are powerful, production-ready options.

However, if you're managing large volumes of cold data, or simply want to avoid paying premium prices for straightforward file storage needs, solutions like Archil offer compelling economics without sacrificing the familiar NFS interface your applications expect and reducing the operational burden on your engineers.

The right choice isn't about maximum theoretical performance, it's about matching your actual requirements to the most cost-effective solution that meets them.

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