Contact Us Menu
Filters
Categories: Insight

Distributed File Systems and Object Storage: Differences and Benefits

What is a Distributed File System?

Gartner defines distributed file systems as follows:

Distributed file system storage uses a single parallel file system to cluster multiple storage nodes together, presenting a single namespace and storage pool to provide high bandwidth for multiple hosts in parallel. Data is distributed over multiple nodes in the cluster to handle availability and data protection in a self-healing manner, and cluster both capacity and throughput in a linear manner.”

Like distributed file systems, object storage also distributes data over multiple nodes in order to provide self-healing and linear scaling in capacity and throughput.

With enterprises set to triple the amount of unstructured data they have stored in the next four years, according to Gartner, enterprises are looking for efficient ways to manage and analyze that data. This trend has spiked a massive shift toward distributed cloud storage and object storage that enable enterprises to scale linearly (scale-out) in a cost-effective manner to address their performance and capacity needs, as enterprises look for efficient ways to cope with the explosion of unstructured data. 

Like distributed file systems, object storage also distributes data over multiple nodes in order to provide self-healing and linear scaling in capacity and throughput. But this is where the similarities end.

While the two technologies are both essential for managing unstructured data, each is a discrete technology with a distinct set of attributes. This post outlines some of the basic differences between object storage and distributed file system storage.

The Differences between Distributed File Systems and Object storage

From a technical standpoint, object storage differs from file systems in three main areas:

  1. In a distributed file system, files are arranged in a hierarchy of folders, while object storage systems are more like a “key value store,” where objects are arranged in flat buckets.
  2. File systems are designed to allow for random writes anywhere in the file. Object storage systems only allow atomic replacement of entire objects.
  3. Object Storage systems provide eventual consistency, while distributed file systems can support strong consistency or eventual consistency (depending on the vendor).

Here’s a side-by-side comparison:

Distributed File System

Object Storage

  • Files in Hierarchical Directories
  • Objects in Flat Buckets
  • POSIX File Operations
  • REST API
  • Random writes anywhere in file
  • Atomically replace full objects
  • Strong or Eventual Consistency
  • Eventual Consistency

Object Storage and Distributed File Storage Capabilities

As noted, object storage and distributed file systems are well suited for storing large amounts of unstructured data. Object storage exposes a REST API, and therefore is limited to applications that are specially designed to support this type of storage. In contrast, distributed file systems expose a traditional filesystem API, which means they are suitable for any application, including legacy applications which were designed to work over a hierarchical filesystem.

Distributed file systems offer a richer and more general purpose (but more complex) interface to applications, which enables them to perform specific operations which are not suitable for object storage. Examples of these capabilities include acting as the backend for a database, or handling workloads that are heavy on random reads/writes.

Object storage, on the other hand, is more suitable for acting as a repository or archive of massive volumes of large files and comes at a significantly lower price per gigabyte than a distributed filesystem.

The CAP Theorem and a Comparison of Distributed File Systems

Not all distributed file storage systems are created equal – and the reason for this is firmly rooted in computer science theory. The CAP Theorem states that a distributed data store can have no more than two out of the following three properties:

  • Consistency: Every read receives the most recent write or an error
  • Availability: Every request receives a (non-error) response – without the guarantee that it contains the most recent write
  • Partition tolerance: The system continues to operate despite an arbitrary number of messages being dropped (or delayed) by the network between nodes

As such, it follows that there are two flavors of distributed file systems on the market today:

Clustered Distributed File System

Consisting of a strongly coupled cluster of nodes, Clustered Distributed Filesystems (DFS) are geared towards strict data consistency and are especially suitable for high scale computing use cases (e.g., big data analytics) at the enterprise core.

Clustered DFS focuses on the Consistency and Availability properties of the CAP theorem. Strong consistency guarantees do not come without a price – they create fundamental limitations on system operation and performance, particularly when the nodes are separated by high latency or unreliable links. Examples of Clustered DFS include products like Dell EMC Isilon and IBM Spectrum Scale.

Federated Distributed File System

Federated Distributed Filesystems are focused on making data available over long distances with partition tolerance. As such, Federated DFS is well-suited for weakly coupled edge-to-cloud use cases such as unstructured data storage and management for remote offices. Federated DFS focuses on the Availability and Partition tolerance properties of the CAP theorem and trades away the strict consistency guarantee.

In a Federated DFS, read and write operations on an open file are directed to a locally cached copy. When a modified file is closed, the changed portions are copied back from the edge to a central file service. In this process, update conflicts may occur and should be automatically resolved. It could be argued that Federated DFS combines the semantics of a filesystem with the eventual-consistency model of object storage.

Edge to Cloud

Examples of Federated DFS include the CTERA Global File System as well as the venerable Andrew File System and Coda developed by Carnegie Mellon in the 1980s.

The following comparison table sums it all up:

Clustered DFS

Federated DFS

  • Strongly consistent
  • Partition tolerant, eventually consistent
  • Deployed in the core
  • Deployed at edge and core
  • Strongly coupled nodes
  • Weakly coupled edge nodes
  • Ideal for high performance computing (HPC); databases; analytics
  • Ideal for archiving; backup; media libraries; mobile data access; content distribution to edge locations; content ingestion from edge to cloud; ROBO storage; hybrid cloud storage

Clustered DFS and Federated DFS both have their places in the enterprise. To maximize benefits from a distributed file system, enterprises need to understand the differences between the two flavors and choose the option that best meets their application needs.

Conclusion

Clustered DFS and Federated DFS both have their places in the enterprise. To maximize benefits from a distributed file system, enterprises need to understand the differences between the two flavors and choose the option that best meets their application needs.
As a federated distributed file system, the CTERA Global File System helps you get all the benefits outlined above, including achieving infinite cloud storage capacity with reduced costs.

It supports a full range of edge-to-cloud file services; enabling LAN-speed file access, modern multi-site collaboration, and comprehensive data protection for users everywhere.

To learn more about CTERA’s Global File System and how your organization can immediately access these benefits, set up a call with a product expert today.

Get a live demo from CTERAs experts.

FAQs

Is object storage better than distributed file storage?
The choice between object storage and file storage depends on your specific needs. Object storage is known for its scalability and compatibility with modern cloud applications. This makes it ideal for storing huge amounts of unstructured data.  While file storage provides a hierarchical file system structure and is better suited for applications that require traditional file operations and strong consistency.

What is object vs file storage in AWS?
The differences, benefits and drawbacks of file versus object storage are well known. AWS offers both of these storage types, through its Amazon Elastic File System (EFS) and Amazon Simple Storage Service (S3) suites respectively.

Why is object storage cheaper than file storage?
Object storage is often cheaper than file storage due to its architecture and cost model. Object storage systems are designed to store and manage large volumes of data efficiently, utilizing commodity hardware and distributing data across multiple nodes. This architecture allows for cost-effective scalability and reduces the need for expensive storage appliances.

Related resources:

 

Get New CTERA Blog Posts Delivered Directly to Your Inbox
Skip to content