Time to read: 4 minutes | Published: March 12, 2025

Disaggregated Storage
What is Disaggregated Storage?

Disaggregated storage is an architecture in data storage systems where storage resources are decoupled or separated from compute resources. This separation allows storage and compute resources to be scaled independently, which can lead to better resource utilization, increased flexibility, and potentially lower costs.


In traditional storage architectures, storage and compute resources are tightly integrated within the same physical server. This can lead to inefficiencies, such as underutilized storage capacity or compute power. Disaggregated storage, on the other hand, uses high-speed networking technologies to connect storage devices to compute nodes. This allows for dynamic allocation of storage resources based on the needs of the compute nodes.

Disaggregated storage is the decoupling or separation of storage resources.
  • Disaggregated storage benefits
  • Disaggregated storage workloads
  • HPE and disaggregated storage
Disaggregated storage benefits

What are the benefits of disaggregated storage?

The key benefits of disaggregated storage include:

Scalability: Storage and compute resources can be scaled independently, allowing for more efficient use of resources.

Flexibility: Resources can be allocated and reallocated dynamically based on workload demands.

Cost-Effectiveness: Better resource utilization can lead to cost savings, as organizations can avoid over-provisioning resources.

Improved Performance: High-speed network connections can provide low-latency access to storage, improving overall system performance.

Simplified Management: Centralized storage management can simplify tasks such as data protection, backup, and disaster recovery.

Disaggregated storage is particularly useful in environments with variable workloads, such as cloud computing, data centers, and large-scale enterprise applications, where the ability to efficiently manage and scale resources is critical.

Disaggregated storage workloads

What types of workloads are best suited for disaggregated storage?

  • Disaggregated storage is particularly well-suited for a variety of workloads that demand high performance, scalability, and flexibility. Some of the key workloads that benefit from disaggregated storage include:
    Cloud Computing and Virtualization
    Cloud service providers and virtualized environments benefit from the ability to scale storage and compute resources independently, improving resource utilization and reducing costs.
  • Big Data Analytics
    Data-intensive applications like Hadoop, Spark, and other big data frameworks can leverage disaggregated storage to handle large datasets efficiently and provide faster data processing and analysis.
  • High-Performance Computing (HPC)
    HPC environments, which require significant compute power and fast data access, can benefit from the low-latency, high-throughput capabilities of disaggregated storage.
  • Artificial Intelligence (AI) and Machine Learning (ML)
    AI and ML workloads often involve processing large amounts of data and training complex models. Disaggregated storage can provide the necessary performance and scalability to handle these demanding tasks.
  • Content Delivery Networks (CDNs) and Media Streaming
    CDNs and media streaming services require efficient storage and retrieval of large media files. Disaggregated storage can help optimize performance and scalability for these use cases.
  • Database Applications
    Relational databases (e.g., MySQL, PostgreSQL) and NoSQL databases (e.g., MongoDB, Cassandra) can benefit from the high availability and performance characteristics of disaggregated storage.
  • Transactional Workloads
    Applications that require high transaction throughput and low latency, such as financial services, can leverage disaggregated storage for improved performance and reliability.
  • DevOps and Continuous Integration/Continuous Deployment (CI/CD)
    Development and testing environments that need to spin up and tear down resources quickly can benefit from the flexibility and agility offered by disaggregated storage.
  • Backup and Disaster Recovery
    Disaggregated storage can enhance backup and disaster recovery solutions by providing scalable and efficient storage for large volumes of data, ensuring quick recovery times.
  • Edge Computing
    In edge computing scenarios, where data is processed closer to the data source, disaggregated storage can help manage storage resources efficiently across distributed locations.
  • Internet of Things (IoT)
    IoT applications generate vast amounts of data that need to be stored and processed. Disaggregated storage can provide the scalability and performance required to handle IoT data.

    Overall, disaggregated storage is ideal for environments where resource flexibility, efficient scaling, and high performance are critical. By separating storage from compute, organizations can better align their infrastructure with the specific needs of their workloads, leading to improved efficiency and cost savings.
HPE and disaggregated storage

What does HPE offer for disaggregated storage?

HPE offers a range of solutions that support disaggregated storage, catering to various enterprise needs for scalable, high-performance, and efficient storage infrastructures. HPE's portfolio includes hardware, software, and services designed to enable and optimize disaggregated storage architectures. Here are some key offerings:

HPE Alletra is a cloud-native data infrastructure that delivers workload-optimized systems. It provides a seamless cloud experience for data infrastructure, whether on-premises or in the cloud. Alletra systems are designed to support a disaggregated storage model with high performance, scalability, and cloud management capabilities.

HPE SimpliVity, while primarily known for hyperconverged infrastructure, can also support disaggregated storage scenarios by decoupling compute and storage resources, providing flexibility and efficiency for various workloads.

HPE Synergy is a composable infrastructure that allows IT to compose physical and virtual resources into flexible pools. It supports disaggregated storage by enabling rapid provisioning and scaling of storage resources independently of compute resources.

HPE Ezmeral is a software portfolio designed for containerized applications and data analytics workloads. It supports disaggregated storage by providing a platform for managing and orchestrating containerized environments, which can decouple storage and compute.

HPE GreenLake is a consumption-based IT model that brings the cloud experience to on-premises infrastructure. It supports disaggregated storage by offering flexible, scalable, and pay-per-use storage solutions.

HPE StoreFabric provides a range of networking solutions designed to optimize storage connectivity. This includes high-performance adapters and switches that enable efficient and low-latency connections between storage and compute resources.

HPE Data Services Cloud Console offers a unified cloud management experience for data infrastructure. It supports disaggregated storage by providing centralized management, orchestration, and automation of storage resources across hybrid environments.

HPE InfoSight leverages AI and machine learning to provide predictive analytics and automated support. It optimizes disaggregated storage by predicting and preventing issues, ensuring optimal performance and resource utilization.

These solutions from HPE provide a comprehensive set of tools and technologies to support and optimize disaggregated storage environments, ensuring high performance, scalability, and efficient management of storage resources.

Related topics

Composable infrastructure

Learn more

Data storage

Learn more

dHCI

Learn more

Hyperconverged infrastructure

Learn more