Dell PowerStore stands out for its high performance, flexibility, and easy integration with VMware. It offers notable data compression and deduplication capabilities while providing powerful NVMe support and machine learning to optimize IT operations.
Dell PowerStore is designed to offer a comprehensive approach to IT infrastructure by enhancing performance and simplifying management. It is particularly suitable for companies that require scalable solutions to increase compute or capacity independently. Featuring built-in intelligence, PowerStore allows efficient storage consolidation and reduced footprint, while integration with CloudIQ enhances monitoring and analytics. However, there are areas for improvement, such as stability, enterprise features, and the user interface. Pricing is high, and support responsiveness needs attention. Organizations primarily use PowerStore for VMware environments, storage, and data protection, supporting high-performance databases and VMware workloads. It is utilized in data centers for disaster recovery and hybrid setups.
What are the key features of Dell PowerStore?
- Flexibility: Independently scales compute or capacity
- High Performance: Offers powerful NVMe support and machine learning
- Integration: Easily integrates with VMware
- Data Efficiency: Provides data compression and deduplication
- Simplified Management: Built-in intelligence for efficient storage management
What benefits should users consider?
- Performance Optimization: Enhance IT operations with machine learning
- Scalability: Increase compute or storage capacity as needed
- Integration Potential: Improve efficiency with VMware and CloudIQ
- Data Protection: Reliable for disaster recovery and hybrid environments
In industries like IT, finance, and healthcare, Dell PowerStore supports efficient data management and enhances infrastructure performance. Organizations leverage it to manage extensive data, streamline virtualization processes, and facilitate migration from legacy systems, while integrating cloud and on-premises infrastructures for improved operations.
In our most recent product, the ActiveStor Ultra, Panasas has developed a new approach called Dynamic Data Acceleration Technology. It uses a carefully balanced set of HDDs, SATA SSD, NVMe SSD, NVDIMM, and DRAM to provide a combination of excellent performance and low cost per terabyte.
• HDDs will provide high bandwidth data storage if they are never asked to store anything small and only asked to do large sequential transfers. Therefore, we only store large Component Objects on our low-cost HDDs.
• SATA SSDs provide cost-effective and highbandwidth storage as a result of not having any seek times, so that’s where we keep our small Component Objects.
• NVMe SSDs are built for very low latency accesses, so we store all our metadata in a database and keep that database on an NVMe SSD. Metadata accesses are very sensitive to latency, whether it is POSIX metadata for the files being stored or metadata for the internal operations of the OSD.
• An NVDIMM (a storage class memory device) is the lowest latency type of persistent storage device available, and we use one to store our transaction logs: user data and metadata being written by the application to the OSD, plus our internal metadata. That allows PanFS to provide very low latency commits back to the application.
• We use the DRAM in each OSD as an extremely low latency cache of the most recently read or written data and metadata.
To gain the most benefit from the SATA SSD’s performance, we try to keep the SATA SSD about 80% full. If it falls below that, we will (transparently and in the background) pick the smallest Component Objects in the HDD pool and move them to the SSD until it is about 80% full. If the SSD is too full, we will move the largest Component Objects on the SSD to the HDD pool. Every ActiveStor Ultra Storage Node performs this optimization independently and continuously. It’s easy for an ActiveStor Ultra to pick which Component Objects to move, it just needs to look in its local NVMe-based database.
