Maximize storage utilization with intelligent data reduction
Today’s virtualized environments can benefit greatly from deduplication and compression. Since much of the data in virtualized environments is duplicate operating system and related data, deduplication and compression rates can be significant.
Inline deduplication can reduce actual data storage requirements by up to 90%. Deduplication conserves valuable storage capacity by computing a hash for new data writes and comparing them against an existing library of hash results. If the hash matches, the data is deemed a duplicate and pointers are stored instead to reference the existing data. Nimbus Data’s deduplication technology is based on crypto-grade hash, using pattern-matching with variable block sizes to ensure the highest level of data reduction.
Lossless inline compression further reduces data storage requirements using an LZ4-based algorithm. The sequence-matching based algorithm is optimized for performance, both in compression and decompression, while providing superior reduction ratios.
Thin provisioning enables administrators to freely share capacity between block and file datastores on the same system. T10-based reclamation is supported for file systems such as VMware’s VMFS. By leveraging thin provisioning, organizations reduce storage costs by improving capacity utilization rates.