The term cloud storage encompasses several storage capabilities available to cloud customers that run on a cloud provider’s hardware. Each of these capabilities meets a different need, but all provide the flexibility to pay only for what you use. The provider is responsible for maintaining the underlying hardware and ensuring that data remains available, resilient, and protected.
The most common types of cloud storage are object, file, and block.
Storage types differ primarily in how they are accessed and the level of performance they provide. The application using the storage and its location determine storage requirements.
Object storage is accessed differently than the other storage types discussed. Software applications must be intentionally written to use object storage by calling web APIs. Object storage is maintained remotely from the application and is used in two similar but different situations. First, it’s often accessed via the internet by applications running on individual computers, mobile devices, and Internet of Things devices, among others. Second, it can be used by applications running in the cloud.
Applications that use object storage can store and retrieve unstructured data from object storage in a remote location without using a file system. The stored items are merely abstract “objects” in the cloud. This means the application developer maintains maximum flexibility and has an essentially bottomless, free-form datastore in the cloud while being charged only for the amount of data stored and transferred.
The downsides of object storage are twofold: It involves a bit more work for the application authors who must manage their own object formats, and there are performance limitations. Object storage is accessed by software making API calls, typically over the internet, so what might take direct-attached storage microseconds and block storage or file storage milliseconds may sometimes take object storage a second or more. For many use cases, such as end users running applications connected to cloud storage on their phones, this performance is acceptable, especially in return for the “anywhere access” these applications provide. And in cases where an application using object storage is running in the same cloud as the objects are stored, performance is considerably higher because all the resources are in the same region on the cloud provider’s own local network.
Archive storage is the ideal solution for storing seldom-accessed data that requires long retention periods. Archive storage is more cost-effective than object storage for preserving cold data. However, unlike other storage options, archive storage data retrieval is not immediate.
Both object storage and archive storage use buckets as logical containers for storing objects. A bucket is a single compartment with policies that determine the actions that can be performed on objects in the bucket—and who can perform them.
When buckets are created to hold data as objects, organizations can decide which default storage tier—archive or standard—is appropriate for their data. Object storage can also automatically move objects to archive storage.
Most traditional applications that run on a physical server and leverage physical drives in your data center use file storage. Operating systems such as Linux or Microsoft Windows Server present the applications that run on them with a file system—a single consistent set of rules and methods for storing and retrieving data. The operating system handles the details behind the scenes—for example, is the physical disk a solid-state drive (SSD)? A traditional spinning disk hard drive? An optical disk? Or a remote network file share? While the operating system takes care of these details, applications simply open, read from, write to, and save files with standardized API calls.
Cloud file storage presents a standard network file share—similar to the network file shares that might run in your own data center—to the operating systems you’re running on servers in the cloud. Those operating systems present that file system to applications running on that virtual machine. Applications don’t need to be modified or changed to run in the cloud; they continue to run with the file storage they’ve always used.
The cloud provider manages the hardware, including physical disks and network hardware, and ensures the data is protected. Additional incremental capacity is available to customers as their needs grow. The inherent advantages of cloud file storage are clear when compared to a traditional approach that involves scheduled bulk purchases of network file systems to meet the needs of future growth and then requires you to manage your hardware and ensure the protection of your data yourself.
Block volumes are like cloud file storage in that they represent an enhanced version of a type of network storage you may already be running in your data center. Using block volumes results in less network overhead and offers higher performance, but it requires more configuration and management within the operating systems in return.
Oracle’s block volumes use a single volume type, which can be configured on the fly with different settings to increase performance or reduce costs. Unlike cloud file storage, block volumes must be configured with a specific size, but that size can be increased at any time while the volume remains online and available to the applications using it.
As with any cloud service, the provider manages the hardware and capacity planning and ensures the data is replicated and protected.
High performance computing (HPC) is becoming increasingly common as more companies use AI, machine learning, engineering simulations, and financial modeling applications. Advancements in recent years have made high performance computing in the cloud possible, easily accessible, and affordable.
However, shared file system throughput for compute clusters has often been a barrier for simulations, AI and machine learning, and complex modeling. But with the right configuration and specifications, all these workloads can be supported.
In Oracle's case, high-performance workloads such as complex modeling thrive because of block storage backed by NVMe SSD media and data centers with fast, flat network architecture. Oracle's block storage performance is also backed by a unique SLA. Learn more in this post from the Oracle Cloud Infrastructure blog.
This type of storage requires the manual creation of file server clusters with cloud compute instances with direct-attached solid-state drives, but it provides the highest levels of performance—the highest throughput and lowest latency—which is required for HPC applications.
For enterprise storage managers, trying to keep up with data growth while juggling data security needs, archiving requirements, and cost-containment issues is like swimming upstream with a pile of physical storage arrays on their backs.
The cloud’s scalability and elastic pay-as-you-grow model mean enterprise storage managers don’t have to shell out for a storage upgrade, whatever the size or granularity—whether it’s a planned or a short-term granular challenge. In addition, consuming cloud services is almost always considered an operational expense and is often a monthly budget line item. Both of these factors invariably make it easier to create and control expenditures.
Here are some of the many use cases for cloud storage solutions across object storage, file storage, and block volumes.
Backup and recovery is the process of storing copies of data to protect organizations against data loss. Leveraging the cloud for backup can protect a copy of your data in a remote location in case of failure or disaster.
Cloud data backup can cement an organization's data protection strategy without increasing their IT staff’s workload. Cloud storage backup services act as an offsite facility for many organizations. There are several approaches to cloud backups that can easily fit into an organization's existing data protection process, including the following: