Software-Defined Storage

Get ready for AI, BI and ML applications

Future-Proof Storage Technology with Software-Defined Storage

In a world of rapidly changing application infrastructure support requirements, Software-Defined Storage (SDS) provides the agility and utilization improvements you need – across IT environments. And it frees your data from hardware constraints, paving the way for the business applications and process of the future.

The ideal solution for new business models

If your business model is based on new technology such as cognitive workloads, big data or analytics, SDS ensures that you can handle launch, scale up and scale down at a fast pace and higher density.

For traditional IT business workloads, too

Even with today’s new business models, traditional IT workloads continue to be an integral part of an integrated infrastructure. SDS can make your enterprise resource planning (ERP), human resource (HR), and customer relationship management (CRM) systems more efficient and more effective.

Why we Make a Fuss About SDS

Our Software-Designed Storage solutions come with a range of benefits. They will help you to:

  • Facilitate IT automation
  • Boost IT agility
  • Optimize systems admin and control
  • Utilize resources more efficiently
  • Fine-tune performance
  • Simplify capacity planning
  • Simplify your architecture
  • Achieve virtually limitless data scaling
  • Support block, file and object data types

Highlights

optimized capacity icon

Gain a competitive edge

With SDS, you can optimize your IT infrastructure, enabling you to provide IT services a higher speed and greater efficiency. And giving you a competitive edge on the competition.

fast speed icon

Faster response times

Supporting your business workloads – AI, BI and ML as well as traditional workloads– requires the fast and efficient delivery of resources. SDS lets you respond to business requests faster and more efficiently.

icon of interconnected cogs

Save time and resources with automation

SDS makes it possible to automate the definition of workloads based on usage patterns and to streamline the allocation of resources accordingly. This saves both time and resources by automating processes that have traditionally been carried out by hand.