What is tiered storage?

Tiered storage is a strategic approach to data management that allocates different types of data across multiple storage media to make the best use of performance, cost efficiency, and accessibility. By categorizing data according to its importance and how frequently it’s used, organizations put their most critical information on the highest-performing storage, while less critical or infrequently accessed data resides on more economical, slower storage media.

In a typical tiered storage setup, the hierarchy involves multiple distinct tiers, each defined by performance characteristics, cost, and reliability. At the top of this hierarchy, mission-critical data requiring rapid access and low latency is placed on premium, high-speed storage, such as flash-based solid-state drives (SSDs). Lower tiers store less essential data on more affordable media, such as traditional hard disk drives (HDDs), tape storage, or cloud-based archival solutions. The lowest tier typically serves as long-term archival storage, where data is hardly ever used. 

This structured allocation lets organizations reduce storage costs by limiting expensive, high-performance media to only the most critical applications, while simultaneously maintaining efficient and reliable access to essential data. Tiered storage forms a foundational component of information lifecycle management, a comprehensive strategy that manages data from creation through archival for the most effective use of resources, as well as regulatory compliance.

What is the history of tiered storage?

The concept of tiered storage originated in the mainframe era, primarily driven by IBM's innovations in managing complex storage requirements efficiently. Initially, storage management involved manually distributing data across various storage devices based on their specific characteristics. During this early period, data allocation relied on serial-attached small computer system interface (SCSI) and serial advanced technology attachment (SATA) drives, optimized through techniques like short-stroking and data striping across redundant arrays of independent disks (RAID).

This early approach created distinct storage tiers, each with unique cost, performance, and capacity profiles, so mainframe systems could effectively handle diverse data storage needs within a unified architecture. Tape libraries complemented this setup, providing a cost-effective solution for long-term storage and archiving of less frequently accessed information.

But this had to be done manually, which was a lot of work. This prompted the development of hierarchical storage management (HSM). HSM automated data placement and movement between storage tiers, dynamically adjusting data locations based on how often the data was used, without having to do it manually. This automation streamlined storage management processes, reducing administrative overhead and using storage resources more efficiently. 

What is multi-tiered storage?

Multi-tiered storage refers to an advanced storage management strategy where data is systematically organized across multiple storage solution platforms or media, each tier serving distinct performance, cost, and availability objectives. Organizations implement multi-tiered storage systems to balance operational efficiency with cost control, strategically aligning storage resources to match the specific requirements and access patterns of different types of data.

Typically, multi-tiered storage architectures are made up of anywhere from two to five or more tiers, determined primarily by an organization's unique data classification strategy. Common data classifications include mission-critical, frequently used "hot" data, less frequently used "warm" data, and rarely used "cold" data. Each classification is assigned to an appropriate tier, such as:

• Tier 0: Ultra-fast storage (e.g., SSDs or storage class memory), supporting critical, performance-sensitive applications (“hot”)

• Tier 1: High-performance, enterprise-grade storage (often SSDs or high-speed HDDs), handling essential but slightly less demanding workloads (“hot”)

• Tier 2: Cost-effective storage (such as HDDs), suitable for backups, disaster recovery, or data analytics (“warm”)

• Tier 3: Archival storage (tape libraries or cloud storage), reserved for long-term data retention and compliance requirements (“cold”)

Organizations are flexible in structuring these tiers, customizing them based on evolving business needs, technological advances, and budget considerations. By allocating data across appropriate storage tiers, organizations get more efficient, faster performance with lower storage costs. 

What is tier 0 storage?

Tier 0 storage represents the highest-performing layer in a multi-tiered storage hierarchy, intended for applications requiring the highest speed and the least latency. This tier supports mission-critical workloads such as real-time analytics, high-frequency trading, artificial intelligence model inference, and intensive healthcare imaging, where delays create problems or increase costs. 

Tier 0 environments typically use ultra-fast storage technologies, including flash-based SSDs, storage class memory (SCM), and in some cases, dynamic random-access memory (DRAM) for temporary high-speed caching. These devices are often connected through advanced interfaces like non-volatile memory express (NVMe) and peripheral component interconnect express (PCIe), which are designed to reduce data access times for higher throughput.

Because of the premium hardware involved, Tier 0 storage carries the highest cost per gigabyte. Organizations, therefore, use it selectively for data that is used most frequently and requires the fastest response. This targeted usage helps those applications run faster and supports business objectives where real-time processing and rapid data availability are paramount.

Incorporating Tier 0 storage helps businesses work better in time-sensitive domains, making them more competitive and reliable in situations where high performance is required. 

What is tier 1 storage?

Tier 1 storage serves as the primary layer for hosting essential business data and applications that require high performance and availability but do not demand the ultra-low latency of Tier 0. It is commonly used for enterprise databases, virtual machine environments, email servers, and other core business systems that must remain responsive and dependable.

While Tier 1 storage is typically slower and less costly than Tier 0, it still relies on robust infrastructure. This tier often includes enterprise-grade SSDs or high-speed hard disk drives configured in RAID arrays for higher reliability. In hybrid setups, flash storage may cache frequently used data while bulk storage resides on HDDs, striking a balance between performance and capacity.

Some Tier 1 environments also incorporate technologies like non-volatile dual in-line memory modules, which combine the speed of DRAM with the persistence of flash. These modules work faster but are still reliable. 

The primary focus at this tier is to ensure reliable access to vital data with moderate latency and high throughput. Organizations choose Tier 1 for workloads that are important for business but more tolerant of latency than the applications designated for Tier 0.

Tier 1 storage plays an important role in keeping the business going, supporting everyday operations, and providing the speed and reliability required by today’s enterprises. 

What is tier 2 storage?

Tier 2 storage is designed for "warm" data—information that is important to retain and use occasionally, but not frequently enough to justify the cost of premium storage. This category includes backups, historical records, business reports, or data used in periodic analytics. It provides a balance between capacity, cost, and accessibility, making it well-suited for secondary storage needs.

At this tier, the focus shifts from peak performance to cost-effectiveness and capacity scalability. Storage media commonly used include traditional HDDs, particularly those using SATA interfaces, and cloud-based storage services. Some Tier 2 environments use backup appliances that collect data from primary tiers so it can be recovered more easily. 

Tier 2 storage is an important part of business continuity and disaster recovery. It often holds copies of Tier 0 and Tier 1 data to restore operations quickly if primary systems fail. Although slower than higher tiers, Tier 2 solutions are engineered for reliability, so essential data is preserved and accessible within acceptable recovery time objectives.

Organizations benefit from Tier 2 storage by offloading less-accessed data from expensive primary systems. This frees up high-performance resources for active workloads while safeguarding important information for future use.

What is tier 3 storage?

Tier 3 storage is dedicated to "cold" data—information that must be kept for compliance, historical reference, or long-term business value, but isn’t used much. This may include archived email messages, legal records, regulatory documents, or completed project files. Because the primary concern is cost, this tier emphasizes low-cost, high-capacity storage solutions over performance.

Common storage media for Tier 3 include slower-spinning HDDs, magnetic tape libraries, and cloud-based archival services designed for long-term retention. These technologies are ideal for storing large volumes of data that can tolerate high retrieval latency. In many cases, data in Tier 3 is written once and rarely, if ever, modified.

Organizations often migrate aging data from higher tiers to Tier 3 storage after it is no longer needed for daily operations. This reduces the burden on more expensive resources while helping meet regulatory requirements for data retention and auditability.

Tier 3 storage plays a vital role in compliance and governance, preserving critical records securely and economically. This tier helps businesses control storage growth and costs while maintaining access to important historical data when needed.

What is automated storage tiering?

Automated storage tiering is a data management technique that dynamically moves data between different tiers of storage based on pre-defined policies and real-time usage patterns. This automation puts the most frequently used data on high-performance storage, while less critical or rarely accessed data is relocated to more economical, lower-performance media, without staff having to do it manually.

Today’s storage systems often include built-in tiering engines that continuously monitor I/O activity and data access trends. These systems use algorithms to reassign data blocks to appropriate storage tiers at set intervals, or in some cases, in real time, without disrupting applications or users. For example, a file that is used often may be moved to SSD storage, while an older, less-used file is migrated to tape or cloud storage.

Automated tiering is especially beneficial in hybrid storage environments that combine SSDs and HDDs or integrate on-premises infrastructure with public cloud storage. It’s more efficient because it keeps “hot” data on high-performance media and “cold” data on low-cost archival systems, but it’s all still available in the storage pool.

Enterprises customize tiering policies based on specific business needs, defining thresholds for how often a storage system is used, data age, or file type. These policies let the storage system align with typical business goals of reducing costs, improving performance, and ensuring compliance.

By streamlining data placement and management, automated storage tiering uses resources more efficiently, reduces administrative overhead, and provides the storage performance users need across the data lifecycle.

What is optimized tiering?

The next level beyond automated storage tiering is optimized storage tiering. While automated storage tiering is reactive, based on use patterns, optimized storage tiering is proactive, based on policy. It involves developing a well-defined taxonomy for data, categorizing it by importance, how often it’s used, and retention requirements, so each data type is assigned to the most appropriate storage tier.

This approach lets IT teams define granular service level agreements (SLAs) and automate storage placement policies based on actual business needs. For example, high-value data might be placed on NVMe SSDs for quick retrieval, while rarely used logs or compliance records might be stored in long-term archival cloud storage.

To implement optimized tiering effectively, organizations must:

• Establish clear data governance policies

• Continuously monitor data usage patterns

• Adjust tiering policies as application requirements evolve

When done correctly, optimized tiering improves storage return on investment by ensuring that expensive resources are reserved only for the most performance-sensitive workloads. It also makes capacity planning and data protection easier by separating transient, frequently used data from static or historical datasets.

Like automated storage tiering, optimized tiering helps businesses meet compliance obligations and performance targets without having to spend too much on storage.

Tiering vs. caching

Although often confused, tiering and caching are distinct data management strategies with different purposes and behaviors.

Tiering involves moving entire datasets between storage layers based on usage patterns and predefined policies. It is intended to put data on the most appropriate storage media according to its importance and frequency of use. Once moved, the data exists in only one location, either a high-performance tier or a lower-cost one. Tiering is intended for managing long-term storage costs and using resources efficiently across a storage architecture.

Caching, on the other hand, creates a temporary, high-speed copy of frequently used data in fast memory, such as DRAM or flash-based storage. Unlike tiering, caching does not move the original data but simply duplicates it to retrieve it faster. This data is managed by algorithms that prioritize the most-used items; once demand decreases, the cache is cleared or overwritten.

Caching is most effective for reading and writing faster in real-time applications, whereas tiering serves to manage data across its full lifecycle. The two techniques are often used together in today’s storage environments: caching improves speed, while tiering supports using storage efficiently over the long term. 

Understanding when to use caching, tiering, or both helps IT teams design efficient storage strategies that balance performance, capacity, and cost.

Get performance at the right price with Aerospike

Now that you understand the fundamentals of tiered storage, it's time to consider how to put this knowledge into action. Whether you're looking to improve latency, reduce storage costs, or meet SLAs, the next step is finding a data platform that delivers both scalability and performance.

Aerospike is built to help enterprises achieve just that. By providing sub-millisecond access to critical data at petabyte scale, Aerospike means your hot and warm data is always on the right infrastructure for the best price performance. With built-in intelligence for real-time data movement and support for hybrid cloud, Aerospike helps you align performance with business value, without spending on storage you don’t need.

If you're exploring how to update your storage architecture or improve data tiering strategies, Aerospike offers a next-generation platform that’s ready to scale with your needs.

Explore how Aerospike can help you meet your SLAs with the right price performance balance.