Quantum StorNext and PeerGFS compete in the data management solutions category. Quantum StorNext seems to have the upper hand in features and deployment, making it a preferred choice for those prioritizing performance.
Features: Quantum StorNext offers robust file sharing and data storage capabilities, high-performance workflows for media and entertainment, and superior scalability for high-demand environments. PeerGFS provides seamless global file sharing, efficient data synchronization, and flexible data access with minimal infrastructure.
Ease of Deployment and Customer Service: Quantum StorNext provides a comprehensive deployment model with robust support, facilitating easy integration into existing infrastructures. PeerGFS offers a streamlined deployment process with efficient customer service but may require more manual setup.
Pricing and ROI: Quantum StorNext involves higher upfront costs but offers significant ROI for businesses needing extensive data management. PeerGFS is more cost-effective with quick ROI, ideal for companies with limited budgets.
| Product | Market Share (%) |
|---|---|
| Quantum StorNext | 5.5% |
| PeerGFS | 4.7% |
| Other | 89.8% |
PeerGFS is a software-only solution developed to solve
file management/file replication challenges in multi-site,
multi-platform, and hybrid multi-cloud environments. With over
25 years of experience in geographically dispersed file replication,
we help organizations:
Improve availability through Active-Active data centers
(on-premises and/or in the cloud)
Protect data at the Edge with Continuous Data Protection to the data center
Increase productivity for distributed project teams with fast, local access to file data
Today’s always-on world requires real-time data infrastructure with 24x7x365 availability. PeerGFS works with the storage systems you already have deployed and support:
High volume data replication between well-connected data centers
Wide area networks with limited bandwidth and higher latency
PeerGFS is easy to install and manage. Different job types can be configured, at a granular level, to support specific application requirements.
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