DataCore™ Parallel I/O

Why buy 10 servers when 2 will do?

I/O Bottleneck Leading to Slow Response? Speed It Up with Adaptive Parallel I/O

Top Reasons for Virtualizing Servers:

  1. Consolidate multiple workloads on a server using its multiple CPUs and large memory
  2. Isolate applications from hardware changes and failures so they run smoothly


All workloads wait on one serial process for I/O (input / output), creating a bottleneck.

Pain Points:

  • More servers required to spread the I/O load—fewer virtual machines (VMs) per server
  • Apps run slower when virtualized
  • Expected cost reductions don’t materialize


Hypervisors, operating systems and container virtualization treat I/O serially even though workloads are scheduled to run in parallel across several CPUs.

The Solution: Unlock the Full Performance of Your Servers with DataCore™ Parallel I/O Software

How: Process I/Os in parallel leveraging multi-core processor systems

Benefits: Do More with Less

  • Far fewer servers needed (2 vs 10)*
  • Apps run 10X faster**, even when virtualized – work completes in 1/10th the time
  • Systems respond quicker without adding hardware
  • Higher workload consolidation ratios – more VMs per server
  • Costs decrease substantially, as does complexity

Proof: World record holder for Performance and Price-Performance

parallel io software solutions from datacore

Product Availability: The Power of Parallel I/O is included in one of our products:

* Ratios depend on number of cores per CPU and I/O intensity of workloads
** TechValidate survey results of DataCore customers

i DataCore SANsymphony 10.0 SPC-1 Full Disclosure Report

Get Started with SANsymphony, Software-Defined Block Storage