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What is Object Storage?

March 27, 2024 | min


What is object storage?

Object storage, also known as object-based storage, differs from other computer data storage architectures in that it lets you manage objects rather than file systems and data blocks. An “object” includes the data itself, some metadata, and a unique identifier. This data can be immediately accessed through APIs or http/https. In this way, the object storage safeguards the data. This data can also be replicated to multiple datacenters if needed.

There are multiple ways to implement object storage: the device level, the system level, and the interface level. Regardless of the level, object storage systems can retain massive amounts of unstructured data (such as text documents, web pages, log files, emails, and sensor data), which constitute the majority of the world's data.

On a general level, an object storage use case commonly supports application developers, who must manage user-created media through object storage. Because object storage can handle unlimited media files and scale to multiple petabytes and beyond without degrading performance, developers and IT admins find it useful for storing unstructured data, backup files, database files, log files, large datasets, archival files, online collaboration files (like Dropbox), and other use cases.
 
Additionally, it's worth noting that object storage also exists in the cloud. Here are some common cloud-based object storage providers: Amazon S3, Rackspace Cloud Files, Microsoft Azure Blob Storage, Google Cloud Storage, and Nutanix Objects Storage.
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File storage vs. block storage vs. object storage

File storage, block storage, and object storage are three common types of storage systems, each with distinct characteristics and use cases. The choice of storage type depends on the specific requirements of the applications and workloads being supported.

File storage

To understand object storage and its similar-sounding storage architectures, it’s important to look at the foundational storage solution first: file storage. File-based storage, like most predecessors, is simple, but limited. Files are named, tagged with metadata, and then organized into folders. The naming process is what makes navigation somewhat simple, and because many companies need centralized access to files, file storage is a feasible option for user directory, department shares, and other shares where navigation of files in a directory is necessary.

File storage also offers a hierarchical system that, with small amounts of data, works perfectly well. And while technically, you can create and store many more files, finding them later in the directory structure may be harder for very large shares. Scanning through endless folders filled with endless files is simply not scalable nor efficient.

Block storage

With that major limitation in mind, it’s time to look at the next level of storage: block storage. Commonly found in SAN architectures, block storage handles a raw storage volume known as a “block,” which includes files that have been split into equal-sized segments of data. From there, an operating system manages these volumes and uses them as individual hard drives, which enables organizations to use third-party tools to manage and back up the data.

Block storage typically offers higher performance than file storage because applications directly access data stored in volumes which are made up of a collection of blocks on disk. This eliminates the overhead of file systems and management. Unlike file storage architectures, the databases or operating systems accessing the volumes determine the storage management strategy, allocating storage for different applications, determining where the data goes, and tracking permissions and access control.

Object storage

Compared to both architectures, object storage is far better suited for large amounts of ever-growing data. It’s much easier to find a specific data set in an object storage architecture. Because each object has its own unique identifier, you don’t need to manually search for a file within a directory. For very large data sets, businesses tend to prefer object storage with its better management at large scale and lower cost of storage. While file storage and block storage architectures can expand, their usability and simplicity decrease as the data grows into the multi-petabyte range.

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Benefits of object storage

Both humans and machines are responsible for generating massive amounts of data, and while some is structured, the vast majority is unstructured. And because unstructured data is difficult to manage and store, businesses are turning to object storage solutions to tackle its unique challenges. Additionally, object storage delivers:

  • Superior searchability - In object storage architecture, the metadata resides in the object itself. That means IT admins don’t need to build databases to merge metadata with the objects. Not to mention, custom metadata can be created, changed, and added overtime. And most importantly, custom metadata makes object storage simple to search through and navigate, unlike its file storage predecessor.
  • Unlimited scalability - Perhaps the most obvious advantage of choosing object storage is its ability to scale limitlessly. Businesses can add nodes as needed and scale horizontally. Because metadata stays with the objects, the system is “flat,” which allows for virtually unlimited scaling when compared to traditional storage methods.
  • Cost efficiency - On the topic of scalability, businesses generating large volumes of data need a system that makes the most sense for their budget. Because object storage scales out easily, it’s far more cost-efficient to store data in an environment without volume and searchability limitations.
  • Better resiliency - Object storage delivers quick, reliable disaster recovery for object files. That’s because when an object is created, it automatically copies onto 1+ nodes. In case a disaster strikes, businesses can rest assured their data won’t be lost.

Object storage use cases

Object storage is versatile and finds application in various scenarios where large-scale storage of unstructured data is required. Here are some common use cases for object storage:

  • Big data analytics - Object storage is a fundamental component of big data analytics platforms. It enables organizations to store vast amounts of unstructured data, including log files, sensor data, and social media feeds. By integrating object storage with analytics tools organizations can perform complex data analysis and extract valuable insights from their data.
  • Cloud-native applications - Object storage is a foundational component of cloud-native applications and microservices architectures. It provides a scalable and durable storage backend for cloud-native applications, enabling developers to store and access data via RESTful APIs. Object storage is often used in conjunction with container orchestration platforms like Kubernetes.
  • Media and entertainment - Object storage is well-suited for storing large multimedia files such as videos, images, and audio recordings. It is commonly used by media and entertainment companies for content distribution, digital asset management, and video streaming services.
  • Backup and archiving - Object storage is widely recognized as a reliable and efficient solution for backup and archiving, offering scalability, durability, cost-effectiveness, and ease of management for organizations of all sizes.
  • Internet of Things (IoT) - Object storage is used to store and analyze massive volumes of data generated by IoT devices, such as sensors, smart meters, and connected appliances. By ingesting IoT data into object storage systems, organizations can derive actionable insights, monitor device performance, and optimize business processes.
  • Collaboration and file sharing - Object storage platforms like Dropbox and Google Drive leverage object storage to provide file sharing and collaboration services to users. Object storage enables users to upload, share, and synchronize files across multiple devices while ensuring data availability and security.

Is object storage right for your business?

It’s estimated that over 80% of all data generated is unstructured, though that percentage may be low. And by 2025, IDC estimates that we’ll have 5 times as much data as we have right now.

Businesses of all sizes must wrangle enormous amounts of ever-growing data, and because growth—especially that of unstructured data—can be unpredictable, their storage solution of choice must be able to quickly and effortlessly scale on demand. With object storage, businesses aren’t just better equipped to store their data—they’re also better able to manage it, search through it, and therefore leverage it for better insights.

Not to mention, compared to its file and block storage predecessors, object storage isn’t limited by a hierarchical organization. Instead, data is organized in a flat plane, providing cleaner, more readily available access than other storage architectures can deliver. Plus, this flat environment is far more customizable—by number, attribute, and more.

Nutanix and object storage

Nutanix Objects Storage is a simple, secure, scale-out object storage solution that helps customers to eliminate complexity and infrastructure silos while protecting enterprise data from ransomware attacks. As a software-defined storage solution, Nutanix Objects Storage delivers extremely fast, secure, S3-compatible object storage at a massive scale to hybrid multicloud environments enabling the use of Object store as a data repository for backups and archives to newer data-intensive, high-performance applications such as Big Data Analytics and AI/ML. A single S3-compatible namespace effortlessly scales to accommodate petabytes of unstructured data without imposing any minimum storage capacity requirements. Nutanix Objects Storage prioritizes performance, scalability and cloud-native support and integrates with analytics platforms and query engines at the edge, core or cloud. 

Explore our top resources

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