An Intelligent & Optimized Way to Access Flash Storage Increase Performance & Scalability of Your Applications
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1 An Intelligent & Optimized Way to Access Flash Storage Increase Performance & Scalability of Your Applications Saeed Raja Director Product Management Enterprise Storage Solutions Corporation August 6, 2014
2 Forward-Looking Statements During our meeting today we will make forward-looking statements. Any statement that refers to expectations, projections or other characterizations of future events or circumstances is a forward-looking statement, including those relating to market position, market growth, product sales, industry trends, supply chain, future memory technology, production capacity, production costs, technology transitions and future products. This presentation also contains forward-looking statements attributed to third parties, which reflect their projections as of the date of issuance. Actual results may differ materially from those expressed in these forward-looking statements due to a number of risks and uncertainties, including the factors detailed under the caption Risk Factors and elsewhere in the documents we file from time to time with the SEC, including our annual and quarterly reports. We undertake no obligation to update these forward-looking statements, which speak only as of the date hereof or as of the date of issuance by a third party, as the case may be. August 2014
3 Legacy Architecture Can Take Limited Benefit of all Flash Storage Traditional Architecture Application Database OS/File System HDD Disk API has no calls for unique capabilities for flash storage Disk API blocks full benefits of flash OS disk code & file system lacks parallelism needed for high IOPs of flash Traditional architecture based upon HDD type memory structure
4 With Flash Adoption Performance & TCO Improve But Full Potential of Flash Storage Still Unrealized Traditional Architecture Application Database OS/File System HDD Traditional architecture based upon HDD type memory structure Traditional Architecture Application Database OS/File System HDD Flash improves Performance & TCO but challenges remain Many applications treat HDD and Flash alike: Replacing HDD with Flash can increase IOPs and performance However, full potential of Flash still not achieved because: 1. Disk API still prevents full use of Flash as it does not have flash oriented calls 2. OS disk code & file system still lack parallelism needed for high IOPs of flash
5 With Applications Get Full Benefits of Flash Storage Traditional Architecture Application Database OS/File System HDD Traditional Architecture Application Database OS/File System HDD Flash Optimized Application/DB Key Value Store ZetaScale Library Operating System SAS, SATA, PCIe ZetaScale API treats flash as memory to enable flash's full potential Highly parallel flashoptimized ZetaScale maximizes flash IOPs ZetaScale works with any flash format, such as SSDs, DIMM, PCIe and NVME Traditional architecture based upon HDD type memory structure Flash improves Performance & TCO but challenges remain Applications get the full benefits of flash memory
6 Flash Storage An Intelligent Way to Access ZetaScale Model Application Key Value Store ZetaScale Library Operating System SAS, SATA, PCIe ZetaScale is an intelligent and flash optimized key-value store Applications place their logical objects into ZetaScale that provides storage subsystem ZetaScale API better exploits flash feature-sets ZetaScale optimizes the use of cores, DRAM, and flash to maximize application performance
7 18 16 ZetaScale MongoDB provides 20x performance improvement over HDD and 3x over SSD 16 16K TPS/Server TPS per server in thousands K TPS/Server K TPS/Server HDD stock SSD stock ZetaScale-MongoDB + SSD 100 Bytes, 10 Cols, 128M Rows - 95% read / 5% write Dell R720 dual socket Intel 2.6GHz CPU, 32 cores, 128GB DRAM (limited to 64GB for test) with 8x SanDisk x210 SATA SSDs single node, Cassandra v1.2.2, ZetaScale v2.0 YCSB (uniform distribution, 128 threads) measurements performed by SanDisk
8 120 ZetaScale provides 9x performance improvement over HDD & more than 2x over SSD K TPS/Server 100 TPS per server in Thousands K TPS/Server K TPS/Server 0 HDD Cassandra SSD Cassandra ZetaScale-Cassandra FDF-Cassandra 100 Bytes, 10 Cols, 128M Rows - 95% read / 5% write Dell R720 dual socket Intel 2.6GHz CPU, 32 cores, 128GB DRAM (limited to 64GB for test) with 8x SanDisk x210 SATA SSDs single node, Cassandra v1.2.2, ZetaScale v2.0 YCSB (uniform distribution, 128 threads) measurements performed by SanDisk
9 140 ZetaScale Cassandra provide major server consolidation for same TPS & C=capacity TPS in Thousands :1 10: : Stock HDD Stock DRAM Stock SSD ZetaScale FDF SSD SSD
10 XAP MemoryXtend GigaSpaces 160 ZetaScale GigaSpaces XAP MemoryXtend provides 2x-3.6x better TPS per dollar FDF-GigaSpaces ZetaScale-GigaSpaces on SSDs on SSDs Stock GigaSpaces in DRAM 121 TPS per dollar No Read / 100% Write 100 % Read / No Write
11 XAP GigaSpaces MemoryXtend ZetaScale GigaSpaces XAP MemoryXtend provides 2x-3.6x better TPS per dollar 50% server consolidation for the same dataset TPS per dollar ZetaScale-GigaSpaces FDF-GigaSpaces on SSDs on SSDs Stock GigaSpaces in DRAM Number of servers : No Read / 100% Write 100 % Read / No Write 0 Stock GigaSpaces FDF-GigaSpaces ZetaScale- GigaSpaces
12 ZetaScale REDIS allows out-ofmemory datasets to run at same or better speed as in-memory datasets >50% server consolidation for the same dataset TPS per server in thousands K TPS/Server 132K TPS/Server Nr of Servers Stock REDIS (DATA < DRAM) ZetaScale REDIS (DATA > DRAM) 0 Stock SSD ZetaScale REDIS
13 Conclusion ZetaScale offers an intelligent and optimized way to access flash storage Applications can achieve significant performance improvement and scalability As a result, datacenter can realize significant TCO benefits
14 Thank You! Keep up to date with the latest on technology trends and news from SanDisk at ITBlog.SanDisk.com SanDisk Booth 204 August 2014
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