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面向大数据的存储系统

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Hanson Dong
Hanson Dong
1 of 11
董唯元 dong.hanson@gmail.com
 大数据背景下存储系统设计需要考虑哪些因素  如何根据企业的具体情况选择合适的解决方案  非结构化数据存储系统设计案例分析  现有可选的大数据解决方案对比分析
基本目标 业务目标 实施目标 •数据容量 •性能要求 •硬件来源 •数据类型 •功能要求 •软件来源 •数据价值 •服务要求 •服务来源
 命名空间  寻址空间  性能保证  迁移/同步  管理模式  备份恢复窗口  故障重建机制
技术前 模型样 沿 板 免费午 服务风 餐 险
 自主技术能力  服务依赖度  风险和价值评估  系统未来发展  业界技术趋势
自我维护 特殊 典型 需求 应用 依赖支持
自我维护 研发维护实力强 技术维护实力强 应用需求较特殊 应用需求较典型 开源平台，自研开发 开源为主，模块组合 特殊 典型 需求 应用 需厂商提供支持 需依赖厂商服务 定制化应用需求 应用需求较典型 商业产品，组合尝试 商业产品，外包集成 依赖支持
自我维护 研究机构 技术组织 技术定型 实验室 首批实践者 特殊 典型 需求 应用 高性能计算 完全商业化 关键性业务 网格/集群 私有云 依赖支持
谢 谢！

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面向大数据的存储系统

  • 2.
  • 3. 大数据背景下存储系统设计需要考虑哪些因素  如何根据企业的具体情况选择合适的解决方案  非结构化数据存储系统设计案例分析  现有可选的大数据解决方案对比分析
  • 4. 基本目标 业务目标 实施目标 •数据容量 •性能要求 •硬件来源 •数据类型 •功能要求 •软件来源 •数据价值 •服务要求 •服务来源
  • 5. 命名空间  寻址空间  性能保证  迁移/同步  管理模式  备份恢复窗口  故障重建机制
  • 6. 技术前 模型样 沿 板 免费午 服务风 餐 险
  • 7. 自主技术能力  服务依赖度  风险和价值评估  系统未来发展  业界技术趋势
  • 8. 自我维护 特殊 典型 需求 应用 依赖支持
  • 9. 自我维护 研发维护实力强 技术维护实力强 应用需求较特殊 应用需求较典型 开源平台，自研开发 开源为主，模块组合 特殊 典型 需求 应用 需厂商提供支持 需依赖厂商服务 定制化应用需求 应用需求较典型 商业产品，组合尝试 商业产品，外包集成 依赖支持
  • 10. 自我维护 研究机构 技术组织 技术定型 实验室 首批实践者 特殊 典型 需求 应用 高性能计算 完全商业化 关键性业务 网格/集群 私有云 依赖支持