EFS vs. S3: Network File Store vs Object Store

Picking the Right Cloud Storage Solution

With so many storage options out there, it’s easy to pick one that doesn’t quite fit, and that can lead to slow performance or a surprising cloud bill. Some services might look similar on the surface, but they’re designed for very different use cases.

Take Amazon EFS and S3: both are powerful, flexible, and widely used, but they shine in very different scenarios.

• EFS is a fully managed, scalable file system that supports shared access over NFS. It’s ideal for workloads that require simultaneous access from many clients and need a traditional file interface
• S3 is AWS’s flagship object storage service—massively scalable, low-latency, and perfect for storing backups, media files, static assets, and more.

In this post, we’ll break down the strengths and trade-offs of each, compare pricing and performance, and explore what to consider when choosing the right option—or combination—for your workload.

It comes down to money

Choosing the right storage option on AWS isn’t just about features, it can have a big impact on your app’s performance and your monthly bill. EFS and S3 are two popular choices, but they serve very different purposes and come with very different pricing models. Here's how they compare:

Amazon EFS vs. Amazon S3 Pricing (May 2025)

What This Means

• EFS is built for shared file access — think multiple instances reading and writing to the same data. It's super flexible, but it’s priced like a premium service.
• S3 is built for scale — it’s way cheaper per gigabyte and shines when storing large amounts of unstructured data (like backups, media, logs, etc.).
• Data transfer costs work differently: EFS charges per GB, while S3 charges per request. Depending on how often you're accessing your data, this can make a big difference.

When it comes to pricing, S3 wins. But performance is where EFS can justify its higher cost, especially for workloads that demand fast, consistent access with file system semantics.

Performance Comparisons

EFS > S3

S3 > EFS

EFS = S3

Reducing Devops Cost

While S3 is more cost-effective from a pure storage pricing perspective, infrastructure decisions shouldn't be based on pricing alone. For many organizations, engineering effort is the most significant cost driver, and that's where EFS offers strategic value.

Amazon EFS supports the NFS protocol, making it well-suited for lift-and-shift migrations. Applications that rely on traditional file systems can move to the cloud with little to no modification. This compatibility enables teams to maintain existing access patterns, directory structures, and permission models, significantly reducing the complexity of migration.

By eliminating the need to re-architect legacy systems for object storage, EFS helps organizations accelerate cloud adoption while minimizing operational overhead. The result is a faster time-to-value and reduced strain on engineering resources.

In scenarios where time, continuity, and maintainability are critical, EFS can deliver substantial cost savings through simplicity and speed, even if the per-gigabyte cost is higher.

Use Cases

S3

Applications often need to store large assets like MP4 videos, high-resolution JPEGs, or other media. In these scenarios, S3 is typically the best option. It’s optimized for storing vast amounts of unstructured data at low cost, making it ideal for large content files where storage efficiency matters most.

Object storage like S3 was purpose-built for these use cases. For example, Celgene uses S3 to store petabytes of genomic backups, leveraging its scalability and affordability to manage critical data at scale.

EFS

Many enterprise workloads—such as ERPs, internal portals, or code repositories—depend on a shared, durable file system. If your application expects a traditional file system, EFS is a strong fit.

These types of apps are often originally built on local or network file storage, so using EFS enables a smoother lift-and-shift to the cloud without major refactoring. It also reduces the operational burden of managing infrastructure.

In fact, in the same case study mentioned above, Celgene used EFS for its R&D workloads, where low latency and high durability were essential.

What About Caching?

In the Celgene example above, you could argue that using EFS for R&D workloads might not be the most efficient choice. That data likely sits idle much of the time, yet Celgene is still paying EFS’s premium pricing. This highlights a common dilemma: do you pay more for EFS’s low latency and simpler DevOps, or save money with S3’s lower cost and higher operational overhead?

There’s no perfect answer, but several tools aim to bridge that gap.

One option is s3fs, a FUSE-based library that lets you mount an S3 bucket as if it were a file system. This makes lift-and-shift migrations easier by reducing the need to rewrite your application. But S3 isn’t a true file system, and s3fs comes with notable limitations—like slow directory listings, no native support for appends or random writes, and a lack of coordination across multiple clients. It works in some cases, but it’s far from a drop-in replacement for EFS.

That’s where solutions like Archil come in. Archil builds a smart caching layer on top of S3, offering the performance and interface of a file system while keeping the cost savings of object storage. It shines in workloads where data is mostly cold but occasionally needs fast, high-throughput access—for example, analytics, machine learning, or R&D environments.

Archil is POSIX-compatible, so it supports file locking and coordination, which helps avoid race conditions—something S3 alone can’t do. It’s a compelling middle ground for teams looking to reduce cloud costs without giving up performance or rewriting their entire stack.

For teams looking to strike a balance solutions like Archil are worth considering. By layering intelligent caching over S3, they offer a practical middle ground for modern workloads that need to scale efficiently without rewriting legacy code.

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