Data storage typically consumes a sizable portion of IT expenses. Cloud-based storage, object storage, and decentralized storage are three examples of the newer forms of data storage technologies that have emerged in response to the exponential growth in the amount of data being generated.
Implementing tiers in storage is a method for making the most of your storage space, backing up your data without wasting time or money, and taking advantage of the most suitable storage technology for each type of data.
Tiered storage is a strategy that involves allocating distinct categories of data to various types of storage media. This method aims to increase the speed and resilience of mission-critical applications while lowering overall storage costs.
Depending on its importance to the company, data in a tiered storage system is organized in tiers according to how frequently users and applications access it. To further organize the data, it is placed into storage tiers that vary in capacity, speed, and media costs.
The quickest and more costly storage media is often reserved for the most crucial data. Data with the highest priority might be stored on a combination of flash SSDs and Intel Optane memory modules in a first, high-performance tier, while data with a lower priority may be stored on traditional disk drives in a second, lower-performance layer.
Then, data that must be maintained perpetually might be archived in a third tier, either on tape drives or cloud-based storage.
Tiered Storage is beneficial for disaster recovery processes. A Recovery Point Objective (RPO) and Recovery Time Objective (RTO) must be established for disaster recovery plans. An ideal system would prevent data loss while allowing instantaneous recovery. This would come at a high price, but storage tiering comes in handy.
Due to its importance, this data must always be kept on the most secure storage tier, where it can support high-throughput applications like customer transactions. Lack of access to this mission-critical data may lead to mediocre output, lost sales opportunities, and other issues that eat into profits. A Data Retention Policy is also beneficial for separating different types of data.