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.
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.
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.
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.
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.
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:
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:
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 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.