Storage tiering is simply the process of optimizing the use of available storage resources. It also enables effective ways to back up data, save on costs, and employ the best storage technology for each kind of data.
Users apply storage tiering to all devices to keep data in to handle information volume growth while incurring as little additional cost as possible. Various kinds of storage, including cloud-based, object, and distributed, can benefit from the strategy.
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Storage tiering can follow different strategies when it comes to storing data. But the primary strategy is to store the most frequently accessed information in the fastest storage device. So if your organization uses various kinds of storage means—Solid State Drive (SSD), magnetic disk drive, and tape storage—you can store the most-used data in the SSD (the fastest) and the least-accessed on tape storage (the slowest).
What Are the Advantages of Storage Tiering?
Storage tiering provides several benefits. We discussed three of them in greater detail below.
Lower On-Premises Storage Costs
Employing storage tiering reduces the need to purchase high-performance storage equipment. It also lessens the amount spent on maintaining and replacing lower-performance and lower-cost storage devices at more frequent intervals.
Ability to Reuse Old Equipment
Storage tiering enables organizations to continue using old equipment instead of decommissioning them. They may still be suitable for less-important data or information that requires archiving.
Reduced Public Cloud Storage Costs
While cloud storage costs less than storing data on-premises, public cloud services still require paying bills based on usage (i.e., gigabytes per month). Storing only data that requires accessibility thus reduces costs. Cost-effective storage devices that don’t require much overhead can be an option for storing data that users only need to retain for record purposes. In this scenario, the public cloud serves as hot storage while cheap but reliable means to store information serve as cold storage.
Cold and Hot Storage, What’s the Difference?
We can classify storage into two types—cold and hot storage. The table below shows their main differences.
Cold Storage | Hot Storage | |
Required access speed | Slow | Fast |
Access frequency | Low | High |
Data value | Low | High |
Storage media | Slow (e.g., tape) | Fast (e.g., SSD) |
Storage location | Can be off-premises | Colocated or readily accessible to users |
Cost | Low | High |
What Kind of Storage Does Each Data Type Require?
For most organizations, classifying storage into hot and cold is not enough for storage tiering. In such cases, the following four data classifications are better suited.
- Mission-critical data: This is required for high-performance applications, especially if delays can cause damage.
- Hot data: This refers to information users constantly require for business applications. While performance is critical, the devices used shouldn’t cost too much.
- Warm data: Users may require this information often but not as much as hot data. Cost is the primary consideration for this type of data, but the storage utilized must have a reasonable access speed.
- Cold data: This information is rarely or never accessed. Users may only maintain it for regulatory compliance. In other cases, they may need cold data to perform big data analytics that isn’t performance-sensitive. They can store this type of information in very low-cost storage devices.
How Can You Apply Storage Tiering Effectively?
The primary consideration when employing storage tiering is to store the most frequently used data in the fastest storage devices. Accessibility is also crucial for this kind of information.
Prioritizing data is, therefore, a must in storage tiering. Classify information in terms of how frequently it is needed or how critical it is to business operations. Archiving doesn’t require high-performance and high-speed devices. It just requires storage that won’t corrupt data when not in use.
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Storage tiering is essential for any organization that holds and uses massive amounts of data, primarily to ensure accessibility and keep costs to a minimum.