In today’s data economy, navigating the many different types of storage can be confusing, especially as the variety and volume of data continues to explode. When architecting a data foundation for innovation, the innate complexity of data storage frameworks and the added nuances of unique business or mission needs can lead to ineffective scalability, performance, and security – not to mention technical inefficiencies and inflated fiscal and environmental costs. Some of the more prevalent data storage types (and terms) include:
Block Storage
Block Storage is a high-performance storage type that divides data into blocks, each managed independently across various environments. It’s ideal for use cases like databases and virtualization where speed and flexibility are critical. The ability to handle large volumes of data with fast access times makes block storage suitable for environments requiring low-latency operations. However, its complexity and cost, particularly in ensuring data redundancy, can be significant. Choose block storage when performance and scalability are paramount.
File Storage
File Storage organizes data in a hierarchical structure of files and directories, making it intuitive and easy to manage for users. This type of storage is perfect for scenarios where collaboration and accessibility are key, such as in shared document repositories or home directories. While it’s user-friendly, file storage can face performance limitations due to single access paths, which might cause bottlenecks under heavy loads. File storage is best selected when ease of use and collaboration are priorities, but not necessarily when high performance is required.
Object Storage
Object Storage is designed for massive amounts of unstructured data, such as multimedia files, backups, or large data sets. Unlike block and file storage, object storage manages data as objects, each with its own unique identifier and extensive metadata. This structure allows for scalable storage across distributed systems and enhanced data retrieval through metadata search. While object storage excels in scalability and managing large volumes of data, it may not be as fast as block storage, making it less suitable for performance-critical applications. Choose object storage when handling large, unstructured data sets and scalability are your primary concerns.
Mainframe Storage
The mainframe is a computing platform developed during the 1960s by IBM for very large batch processing workloads to support government and corporate business functions. Due to the size and expense of mainframe systems, only very large institutions and governments still maintain/use mainframes. Data storage supporting mainframe systems are robust and performant to meet high duty and mission critical requirements. Thus, mainframe storage can be very costly and hard to manage due to the limited availability of skilled technicians and engineers that can support a mainframe environment.
Software-Defined Storage (SDS)
Software-Defined Storage (SDS) can encompass block, object and file storage – and as a consumption model can be better compared to a streaming service like Netflix or Spotify. Instead of owning DVDs or CDs, you access a variety of movies, shows, or music through an app. The content is stored somewhere, but there is a need to worry about where or how it’s stored. SDS lets you access and manage storage without being concerned about the physical storage hardware. This type of storage is ideal for modern data centers, hyper-converged infrastructures, and cloud environments; organizations that require flexible and scalable storage solutions. However, it can require significant initial setup and may involve management complexity, with performance varying depending on the underlying hardware.
One Data + Control Plane
We believe that the future of data storage is simple, sustainable, and performant. Data platforms offer a centralized and scalable way to store, manage, and analyze data regardless of its location. By integrating seamlessly with hybrid cloud environments, data platforms empower organizations to break down data silos and unlock the true potential of their data.
In particular, the new Virtual Storage Platform One represents a simplified approach to managing mission-critical workloads at scale, delivering a unified architecture to efficiently manage the challenge of growing data volume, variety, and velocity by providing one control plane, data fabric, and data plane across block, file, object, cloud, mainframe and software-defined storage workloads – addressing all environments and accelerating data-driven innovation by removing the complexity of data management for storage administrators and CIOs alike. By eliminating infrastructure, data and application silos, the VSP One family of offerings from Hitachi Vantara Federal empowers federal agencies with a trusted data foundation that enables them to consume the data they need, when and where they need it.
This blog article was published in partnership with Carahsoft Technology Corporation.
Learn More:
- eBook: Anything is Possible with the Right Data Foundation
- Research: Federal Data Maturity Report
- On Demand Webinar: Anything is Possible with the Right Data Foundation