We live in a vast and ever-expanding data cosmos. Right now, according to Domo’s Data Never Sleeps 7.0 report, there are 40 times more bytes of data than there are stars in the observable universe. Forbes has estimated that over 2.5 quintillion bytes are created each day, and IDC predicts the amount of data generated annually will top 175 zettabytes by 2025.

Moreover, unstructured data makes up most of this universe: text docs, images, media files, streaming IoT data, PDFs, emails, and such. A staggering amount of new data is created each minute, and the rate of growth only accelerates as each subsequent minute passes.

Facing the Unstructured Data Tsunami

Unstructured data now makes up at least 80% of the information in industries like healthcare, entertainment media, and others. As IT teams become more data-centric around analytics, machine learning, and AI, they must find a more scalable, reliable, and cost-effective solution for storing massive amounts of unstructured data. Unfortunately, when you place data in traditional file storage systems, it becomes tough to search for, edit, and analyze. In fact, according to IDC, more than 90% of today’s unstructured data is never examined.

Enter software-defined object storage. Object storage systems manage and manipulate distinct units called data objects, which combine all the pieces of data that make up a file, along with relevant metadata and a unique identifier. Unlike hierarchical file storage systems – made up of nested tiers of folders in a tree structure – object storage keeps data in a single repository, a flat address space called a storage pool.

Object storage delivers several compelling advantages, especially for API-driven applications associated with a sizeable unstructured data repository.

1. Infinite scalability. Just keep adding data forever with no limit.
In traditional storage methods that use files and tables, data retrieval becomes more difficult as file volume increases. By contrast, object storage easily accommodates growth with no increase in complexity. It quickly scales to handle petabytes of data by simply adding nodes, transcends geographic boundaries in a single namespace, and incorporates more useful metadata. Because it uses HTTP as the primary protocol, object storage pools provide virtually infinite storage for cloud-based SaaS applications, with no limit on the number of objects, file size, or system capacity. Even better, as you add nodes to an object storage cluster, processing and I/O capacity increase in parallel.

2. Fast data retrieval. Free your apps from slogging through database tables and file systems.
Because there is no folder structure, it’s not necessary to know an object’s exact location to retrieve it. Each object has a unique ID and HTTP URL used to retrieve it from the storage pool. With object storage, finding what you need is like picking up your dry cleaning. You don’t need to know precisely where your laundry is. You just need the ticket. Additionally, you can perform read and write operations simply, without ever having to go through a server app.

3. Better analytics. Optimize your resources and customize your policies.
While file systems limit metadata to file attributes only, objects attach any and all pertinent information. This enhanced metadata, along with multiple classification levels, is key to executing in-depth analyses of the use and function of data objects. Create custom policies for data management based on factors such as an object’s replication status, the type and importance of the application it is associated with, and the level of data protection it requires. Establish triggers for actions such as moving an object to a different tier of storage or geography – or for deleting it.

4. Affordable reliability. Protect your data while lowering your overhead.
Unlike traditional file systems, object storage uses nearly all device capacity, resulting in a highly durable and affordable solution. Moving to the cloud drives costs even lower. For instance, you may be able to realize new efficiencies – and, therefore, savings – with an Amazon Web Services S3 storage tier, which delivers additional data protection while performing more expensive data operations against locally managed copies.

When all files are globally available anytime, anywhere, it obviates the need for separate backup applications and calms worries about meeting backup windows and recovery time objectives. By replicating data to geographically dispersed cloud nodes, object storage tolerates multiple simultaneous failures, even entire site losses and regional disasters. Policy-driven hierarchical erasure coding ensures corrupted data objects are able to be restored by reconstructing the data pieces using information stored elsewhere in the array.

Master Unstructured Data with NetApp’s StorageGRID
At Veristor, we solve the complex challenge of ever-expanding storage needs with NetApp StorageGRID. Together, we simplify secure, durable, and affordable object storage for unstructured data at scale in the private and public cloud. It offers infinite scalability, delivers faster data retrieval, and enables superior data analytics driven by rich metadata and classification.

To learn more about how to master an expanding universe of unstructured data with NetApp’s StorageGRID software-defined open S3 storage, check out our infographic here.