真實(shí)譯文展示（如有保密內(nèi)容均以XX替代）
Sample of real translation (Confidentiality retained with XX)
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推動(dòng)傳統(tǒng)IT架構(gòu)向更高效、更靈活并具有更低成本的方向發(fā)展
Enabling the traditional IT architecture to operate more efficiently and flexibly at lower cost
Memblaze針對(duì)虛擬化提供全閃存解決方案和混合存儲(chǔ)方案，全閃存方案中NVMe SSD既是系統(tǒng)的緩存，同時(shí)數(shù)據(jù)也將長(zhǎng)期存儲(chǔ)在NVMe SSD中?；旌洗鎯?chǔ)解決方案中，NVMe SSD作為系統(tǒng)緩存，提高虛擬化系統(tǒng)處理IO的能力，而主存儲(chǔ)由傳統(tǒng)磁盤(pán)承擔(dān)。
Memblaze offers both the all-flash storage solution and hybrid storage solution for virtualization. Regarding the all-flash storage solution, NVMe SSD, in addition to serving as the system cache, is used for long-term data saving. When it comes to the hybrid storage solution, as the system cache, NVMe SSD enhances the virtualization system’s ability to process IO, while the task of main storage falls on traditional disks.
保障海量數(shù)據(jù)高效存儲(chǔ)，降低企業(yè)成本
Ensuring efficient storage of mass data to reduce business cost
大數(shù)據(jù)數(shù)據(jù)量巨大，對(duì)基礎(chǔ)架構(gòu)IO性能有極高要求。NVMe SSD可以提高大數(shù)據(jù)分析系統(tǒng)性能，將IO響應(yīng)延遲降至微秒級(jí)，從而使大數(shù)據(jù)所需要的實(shí)時(shí)分析成為現(xiàn)實(shí)。
Given the enormous amount of data that big data involves, extremely high I/O performance of the basic architecture is required. NVMe SSD can improve the performance of the big data analytics system, and reduce the I/O response latency to the microsecond level, so as to realize the real-time analysis demanded by the big data.
高吞吐，高能效SSD滿(mǎn)足邊緣數(shù)據(jù)內(nèi)容快速處理
SSD with high throughput and efficiency drives fast processing of edge data and content
邊緣中心需要的是在有限空間內(nèi)構(gòu)建高吞吐能力的系統(tǒng)，并且需要24x7不間斷運(yùn)行。SSD可助力大規(guī)模終端數(shù)據(jù)在邊緣數(shù)據(jù)中心完成收集、去重及處理，減少了上傳云數(shù)據(jù)中心的數(shù)據(jù)量，有效緩解了云數(shù)據(jù)中心的存儲(chǔ)和帶寬壓力。
Edge data centers require a 24/7 uninterruptible system that can build high throughput capacity in a limited space. Collection, de-duplication and processing of large-scale terminal data can be conducted in the edge data center through the SSD, which cuts down the amount of data uploaded, thus effectively alleviating the storage and bandwidth pressure on cloud data centers.
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