Facebook set out to develop innovative data center and data center server solutions that were both energy- and cost-efficient. In an unprecedented move, Facebook decided to share its designs with the larger community in an effort to promote and encourage power efficiency and future innovation. The Open Compute Project (OCP) was born from this desire and officially launched in April of 2011.

The goal was to build one of the most-efficient computing infrastructures at the lowest possible cost. Custom-designed servers and storage solutions were built from the ground up and shared with the community to promote continued innovation. The result of these efforts are data centers full of vanity-free servers that are up to 38% more efficient and up to 24% less expensive to build and run than traditional server hardware.

Hyve Solutions, The Leader in OCP Solution Deployment

Hyve Solutions is a Platinum OCP Solutions Provider and the original OCP solutions provider, having built all of the servers and racks for Facebook’s Prineville, OR,  Forest City, NC and Altoona, IL  data centers, and is your best choice for deploying OCP hardware throughout the world. We provide our global customers with customized, purpose-built data center servers and storage solutions that are cost effective and built to be specific to actual workloads and data center environments.



OCP servers were designed for the hyper-scale data center, and are among the most-efficient, scalable systems in the world.

Cost Efficient

One of the major design goals of OCP was to build out a data center at the lowest possible cost and reduce both CAPEX and OPEX expenditures. This goal is realized by removing many unused features found on traditional motherboards and delivering efficient, cold-aisle servicing within a vanity-free design.

Energy Efficient

Energy efficiency is what OCP is all about. OCP servers are capable of being up to 38% more power efficient than traditional server hardware. This is due in part to the innovative method in which power is received and distributed to servers and storage within the rack. Fewer conversions of power are required, leading to more effective Power usage Efficiency (PuE).