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3Par Scores Another First With Enterprise Sub-Volume Optimization

On March 8, 3Par announced their introduction of Adaptive Optimization for sub-volume storage tiering along with their support for SSD's within the InServ arrays. Looking back at my comments in my blog post of January 30th, it is clear that 3Par has moved past EMC with first-to-market positioning with sub-volume data optimization for enterprise-class storage arrays.

3Par announced Adaptive Optimization software for autonomic, sub-volume storage tiering on 3Par InServ F-Class and T-Class storage servers. They also announced support for the STEC MACH8IOPS Solid State Drive (SSD). The MACH8IOPS drive is a new class of cost and power-efficient SSDs. In essence, the announcement now enables 3Par customers to enable automated data movement between SSD, Fiber Channel and SATA drives (3Par calls these Nearline drives). 

3Par's positioning is that they are first to deliver autonomic storage tiering for enterprise and cloud datacenters. Simply put, 3Par is correct in their claim of being first to deliver the greatly anticipated sub-volume tiering for large scale Enterprise deployments. Other storage companies, such as Compellent with its Data Progression software, have provided storage-tiering capabilities, however, this has been across a broad spectrum of mid-range company storage deployments.

We may see both 3Par and Compellent battling it out in the press over first-to-market claims. However, there is a distinction between mid-range and enterprise, and from all indications, it appears 3Par is set to deploy Adaptive Optimization across a wide range of Enterprise customers with I/O intense mixed workload environments and highly complex configurations.

In a conversation with Rob Commins, director of Product Marketing at 3Par, it became clear that the company has been focused on delivering Adaptive Optimization for some time. Rob states that "traditionally, there has been a natural tension between dollars per GB and dollars per IOP, and enterprise customers have had to make costly trade-offs between the two. Adaptive Optimization helps to relieve that tension."

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