Is Object Storage the Best Option for Managing Massive Unstructured Data Growth?
These five reasons point to yes
Today, organizations of all sizes are producing large volumes of unstructured data on a regular basis, driven by a rise in streaming applications, IoT deployments, and high-resolution video and images. In fact, International Data Corporation (IDC) predicts that 80% of all data will be unstructured by 2025. The need to use the right storage architecture to manage and protect large data sets is more important than ever.
Object storage is rapidly replacing storage area networks (SAN) and network-attached storage (NAS) because of its innovative properties that allow enterprises to easily manage immense data sets.
Below is a list of five main advantages object storage offers.
1) Scalability without complexity
Given rapidly growing data volumes, it’s not surprising that storage capacity is a top challenge facing most organizations that generate and use vast amounts of unstructured data. Traditional storage systems were designed with an upper limit on capacity. To accommodate capacity growth, organizations had to buy more storage infrastructure and stack it on top of their existing infrastructure. This approach worked when unstructured data was growing linearly, but it’s cumbersome and inefficient for addressing the exponential data growth occurring today.
Object storage eliminates this scalability limitation. The architecture stores all data as objects in a flat address space — to grow deployments, you simply add nodes to that flat address space. By taking a scale-out approach rather than the traditional scale-up approach, object storage makes it possible to reach exabyte-level capacities without disruption.
2) A single storage pool that can span the globe
With the advent of IoT, remote sensing technologies, and low-cost 4K cameras, continuous streams of unstructured data are now created in real time everywhere. In addition to scalability challenges, this paradigm shift places new demands on storage networking technologies. Object storage addresses this challenge with a distributed system in which nodes may be deployed wherever needed. This makes it possible to perform analytics where the data is collected, rather than having to send all the raw unstructured data across the network for processing.
Seamless cloud integration
Most organizations today plan to use both public cloud and on-premises storage. As a result, analysts predict continued rapid growth for both storage models. Object storage speaks the language of the cloud via its support for the S3 API, the de facto standard protocol for object storage both on-prem and in public clouds.
Because of object storage’s support for S3 and its incorporation of data management features to simplify data placement, public cloud and on-prem storage become two parts of a single global namespace. This means that object storage makes it simple to integrate public cloud and on-prem environments, so organizations can easily move data between the two and always have the option to expand on-prem deployments to the cloud.
Robust metadata capabilities
Metadata is data about data. It can describe anything: when a piece of data was created, who created it, and where it was created, as well the content of that data with as much detail as needed. Metadata makes it much easier to search data, so organizations get more value of out that data via efforts like big data analytics and developing AI/machine learning (ML) models.
Object storage has rich metadata tagging capabilities built in, unlike NAS, which has very limited metadata, or SAN, which has none. Furthermore, object storage provides for fully customizable metadata and can accommodate a limitless amount of it. For example, an X-ray could include metadata that identifies the patient’s name, age, injury details, and which area of the body was X-rayed, making it much easier to locate specific X-ray data.
Tremendous cost savings
Traditional enterprise storage acquisition cost per unit of capacity tends to increase as scale increases — rather than getting a volume discount, you actually pay more. But object storage systems become less costly with scale. One reason is that object storage is a peer-to-peer architecture that remains consistent as you grow. Every node is a controller, so you never have to add (or manage) separate controllers. The only thing that changes as you grow is that data protection becomes more efficient with added nodes, thus driving costs down.
Furthermore, object storage is built on industry-standard hardware, eliminating the need for proprietary platforms and keeping both acquisition and maintenance costs low. As your system grows, the open systems model ensures that your costs always remain in line with the industry’s best pricing. You never have to pay inflated prices for outdated gear.
There’s also lower management costs. Traditional storage becomes complex to manage as the number of systems and associated middleware tools grows. Object storage consolidates data to a single system and leverages built-in management tools, such as automated DR between sites, making it cheaper to administer.
Object storage is the best option to support rapidly growing unstructured data due to its scalability, flexibility, public cloud compatibility, robust metadata, and cost savings. As big data analytics, AI, and ML become increasingly important, it’s critical for organizations to be able to easily manage and access these vast quantities of data. Object storage is a unique storage architecture that has come of age during the cloud era, delivering capabilities that meet the needs of geographically dispersed, cloud-connected enterprises that face skyrocketing data volumes.