Why Management SDS is on Gartner’s Growth List
Posted in tech
It’s no secret that enterprises have more data than they can now manage manually. Industry analyst firm Gartner highlights the urgent need for a solution in its Hype Cycle for Storage Technologies 2017 report, which features Primary Data as a vendor in the Management Software Defined Storage (SDS) category. The category is one of the few rapidly accelerating in growth and adoption, as Gartner notes that “Management SDS's ultimate value is to provide broad capability in the policy management and orchestration of many storage resources.”
DataSphere was architected to help enterprises easily adopt Management SDS from a single storage- and protocol-agnostic software solution. Let’s take a closer look at what makes it an ideal choice for automating data management.
Seamless Mobility on Your Choice of Storage
Calling out what to look for in SDS, Gartner notes that “some management SDS products are focusing on enabling provisioning and automation of storage resources, more comprehensive solutions feature robust utilization and management of heterogeneous storage services, allowing mobility between different types of storage platforms on-premises and in the cloud.”
The DataSphere open-standards-based architecture leverages NFS v4.2 to virtualize data so that it can be moved transparently, according to IT-defined objectives for performance, protection, and price. DataSphere’s machine learning metadata engine analyzes performance telemetry from clients to make intelligent and application aware management decisions, in real time – a unique capability in the market.
Continual Performance and Capacity Optimization
Performance is critical to IT and, notably, Gartner reports that some SDS products can “reduce storage response times, improve storage resource utilization and control costs by deferring major infrastructure upgrades.”
DataSphere optimizes performance in several ways, including:
- Moving the control path out of the data path, giving data native access to storage. Applications directly access storage devices containing the data, rather than passing through a gateway or agent
- Enabling workloads to be dynamically load balanced across multiple storage systems
- Proactively redistributing data to avoid resource contention, protecting performance SLAs
DataSphere also optimizes capacity utilization, tiering data across different storage systems to ensure that data is on appropriate storage for its Service Level Objectives (SLOs). The savings enterprises can achieve by moving warm and cold data off their most expensive storage systems, while seamlessly integrating on-premises object or public cloud storage as an active archive, can literally reach millions. Customers can use our non-invasive Data Profiler to see exactly how much savings they might achieve based on their actual data usage.
Gartner shows Management SDS in a growth phrase in the Hype Cycle, and partners such as NetApp, HGST, and Scality are currently using DataSphere to give customers intelligent data management across their rich storage portfolios. We’re proud to be working with some of the most innovative companies in the world to help them improve performance, optimize capacity utilization, and automate data management across heterogeneous storage.
To learn more about how DataSphere can accelerate your data management innovation, connect with us at email@example.com.